AI tips & trends

Before Sturdy, we worked for a B2B SaaS Software company called Newton. At Newton, we spent an enormous amount of time tracking and recording customer insights that came from customer feedback. 

‍

In fact, we had a training program, Alchemy, where every person at Newton was trained on what to do when they read or heard certain things like, “how do we download our data?” or “can we get a copy of our contract?”. We had a rule that every “happy” customer was sent to marketing for a potential reference. Every unhappy customer got a call from an executive. We thought we were a well-oiled machine. And yet, with all this, whenever we wanted to get on a call with an important customer, we needed to get several people in a room to discuss the account because we could never be sure what state the account was in.

‍

The challenge was that logging and identifying these important account triggers was entirely manual. If we logged every email, it just became noise. If we logged nothing, we had no idea what was going on.

‍

And at Newton, we realized that in a year, we generated 15,000 support tickets, 15,000 phone calls, and almost 100,000 customer conversations via email. 

‍

Email. Almost every executive knows they have data gathering digital dust in email inboxes. Unread messages, Bug Reports, Cancellation Requests, and Unhappy sentiment are just a few examples of critical business signals that flash in and out of inboxes daily. The challenge is, and always has been, to ensure that every signal is recognized and acted on.

‍

When we started Sturdy, the idea was simple, “the way we record and monitor customer feedback is insane. It has to change”. So we decided to tackle customer email first. Along the way, we realized we had built the first “Customer Email Intelligence Platform.” 

‍

‍

In building Sturdy, we learned that a customer email intelligence platform must do four things very well, all at once: 

‍

1. Safely and securely extract only customer emails while ignoring all other emails;
2. Accurately merge all of a customer’s information into one view, a “single pane of glass”; 
3. Classify, categorize and Identify critical themes, topics, and sentiments in each email;
4. Route and alert the teams and teammates who need to know.

‍

Safely and securely extract only customer emails while ignoring all other emails

‍

For a long time, technologists have developed technologies that attempt to extract customer email data from an inbox and put it somewhere more useful: Outlook plugins, BCC addresses, Salesforce logging, Activity Capture, and Do-Not-Reply Email Addresses. These systems often create more issues, like duplicated data, missing emails, and lost headers. 

‍

Modern CEI solutions will not rely on “hacks” like BCC to get customer emails. At Sturdy, we have a patent-pending suite of tools that ensure only emails from/to customers can be ingested. This toolkit also allows Administrators to ask Sturdy to ignore emails sent by certain people, or it can be restricted at the API-level. 

‍

Bottom Line: Extracting customer emails needs to be rock-solid, secure, and highly configurable.

‍

Accurately merge all of a customer’s information into one view, a “single pane of glass”

“Hey, I need to call Acme Corp. Let’s all get together for 20 minutes to review their account.” Having all your customer emails in one organized spot will make wonderful things happen. The most obvious and time-saving will be the virtual elimination of the “hey, what’s going on with this account meeting?” Getting together to discuss accounts will never go away. But, having a 20-minute meeting so everyone can share their email inboxes should.

‍

In fact, Sturdy estimates that in a typical B2B SaaS company, an Account Manager spends almost 30 hours per month in Account Review meetings. 

‍

Bottom Line: Moving customer email out of the inbox will vastly improve account management and add time to everyone’s day.

‍

Classify, categorize and Identify critical themes, topics, and sentiments in each email

‍

The third pillar of CEI is where the heavy lifting happens. Today, your business can convert and categorize every piece of customer feedback into something actionable or insightful, at scale, without manual labor.

‍

If you're considering using AI or machine learning, remember that almost all language models today are trained using consumer data. This means they weren’t trained using business language, which tends to be far more restrained and professional. 

‍

We have reviewed over 10 million customer emails at Sturdy and built language models identifying the key themes and topics driving B2B SaaS and Services businesses. We have found that over 20% of customer emails have an essential theme or topic relevant to another business team. 

‍

Bottom Line: Modern AI technologies will illuminate insights, topics, and themes in your customer base at scale.

‍

Route and alert the teams and teammates who need to know

‍

You have likely worked in a company that attempted an early version of email intelligence. It was just done manually.  “If you get a feature request in an email, log it to Jira and forward it to the engineering team.” Identify, Classify, and Route. Manual labor doesn’t scale.

‍

Imagine if every time a customer was confused by a product issue, it could be routed to the design team. Imagine if every bug report ever reported by a customer was searchable at its source. 

‍

As modern Customer Email Intelligence identifies and routes business themes and topics without requiring human interaction, the hidden costs of recording, saving, and logging customer requests will go to almost zero.

‍

Sturdy’s automation engine allows our customers to harmonize email intelligence with CRM data. So you can say, “If one of our top accounts requests a copy of their contract, let the CEO know.”

‍

Bottom Line: Customer Email Intelligence will ensure that the correct information gets to the right team every time.

‍

Customer email intelligence. The time is now.

‍

There’s never been a better time to upgrade your tech stack to include Intelligence solutions. Businesses can maximize productivity and accuracy by scaling these intelligence solutions while eliminating mundane and time-consuming tasks. This type of automation allows companies to scale quickly, adapt to changing markets faster, reduce costs and increase efficiency. New technologies like Customer Email Intelligence also allow for more intelligent decisions that can save time and money in the long run. Sturdy might be your solution if you want to understand your customers better at scale and remove manual labor from your business. Let us know.

‍

‍

Whether it’s a positive review or a scathing complaint, customer feedback is critical to the success of every business. It’s a window into the experiences buyers seek and a way for B2B software companies to improve their products, processes, and relationships.

‍

Customer feedback is information given by your customers about the quality of your products and services. Are you meeting customer requirements and delivering value? Whether good or bad, there is no better and more reliable data source about your company than customer feedback.

‍

With B2B buyers demanding more B2C-style experiences, it’s never been more critical to keep up with the changing needs of buyers and users. Unfortunately, many teams still rely on yesterday’s tools to solve today’s challenges. 

‍

To date, most companies have relied heavily on surveys to gather feedback. Others have coupled surveys with analytics tools that analyze customer sentiment. Unfortunately, both surveys and sentiment analysis fail to provide the necessary depth of qualitative data to build deeper customer relationships. Simply put, surveys and sentiment are often subject to broad interpretation. 

‍

Today’s most competitive B2B SaaS companies are putting deeper contextual insights about their customers to work. They are doing this by layering them into operations, processes, metrics, information flows, etc., to enable every team to make decisions based on specific, actionable signals. We’ll explore this more later.

‍

Surveys are still the status quo

‍

Let’s face it, surveys are a relatively simple and inexpensive way to collect customer feedback. However, Forrester reports that surveys capture between 2% and 7.5% of customer interactions.

Given the importance of understanding our customers, SaaS businesses must expand their approach to collecting and curating customer feedback. This starts with expanding the data sources teams use to operationalize insights across the business.   

‍

Easier said than done. To date, B2B SaaS businesses haven’t invested heavily enough in tools and technologies to help them better understand their customers. Today, leaders still struggle to create a complete picture of customer needs, frustrations, and intent. To a large extent, this is due to a reliance on surveys.

‍

While many of us can’t rid ourselves entirely of surveys, they continue to fall short for these reasons.

1. Surveys are a backward-looking tool in an era where customers expect near real-time remedies.
2. Survey results are often ambiguous, failing to reveal the cause of customer frustration.
3. Survey data is often seen as unreliable and not contextually substantive enough to drive real business impact.
4. Surveys are often answered by users with exceptionally positive or negative experiences.
5. Survey responses are limited to structured questions, so respondents cannot provide feedback about topics that are not covered. 
6. Surveys require significant customer time and effort and can be considered annoying.

‍

Customer surveys are just one tool in the burgeoning field of customer intelligence. Sturdy defines it as the process of collecting and analyzing customer data from internal and external sources to unlock customer insights. Recently, many have turned to sentiment analysis to gain a deeper understanding of the consumer mindset. Sentiment analysis insights gathered from different sources lead to improved product features, pricing, customer experience, and overall customer satisfaction. 

‍

Sentiment alone is… OK

‍

Many companies are running sentiment analyses on their product or customer service feedback. But as with surveys, this isn’t enough. Sentiment analysis gives you the binary answer good/bad or extends the range with outputs like terrible/bad/OK/good/great. 

‍

Sentiment analysis requires machines to be trained to analyze and understand emotions as people do. Human language cannot be categorized into only three buckets (positive, negative, and neutral) in its intricacies and complexities. For example, Let’s say we determine that 68% of customers have a negative impression of our product. That still leaves us with many unanswered questions: Do we change the pricing? Do we make UX adjustments? Without more specific insights, we’re left, once again, to go with our guts. Think survey results. 

‍

Let’s put it differently: if 68% of your customers are expressing negative sentiment, you need to understand why the customer feedback is so negative. Your team will need contextual clues to solve this level of dissatisfaction. The answers are probably right there; you just need the qualitative layer below the actual sentiment. 

‍

Once you understand the qualitative data, you can design better products, adjust processes, and build better relationships based on specific data points that need less interpretation. To do this, companies are leveraging next-generation AI, NLP, and ML technologies that provide deeper, actionable insights about their customers. 

‍

Tapping a new source of customer feedback

‍

Customer insights programs are more successful when customer data and feedback are gathered from multiple sources to get a more complete, diverse look into customer needs and impressions. Companies realize that customers constantly send signals that help us predict churn, capture references, get in front of renewals, prioritize features, and run our businesses better. Our customers are giving us this information in Slack, Email, Salesforce, Webinars, training sessions, quarterly business reviews, Zoom calls, etc., daily.

‍

Customer Signal

(noun) A gesture, action, or transmission delivered intentionally or unintentionally by a customer that conveys information, instructions, or insights. 

‍

For B2B SaaS businesses, these signals are immensely valuable. For example, reducing churn from 10% to 9% in a $10 million ARR business means that every customer is worth $17k more in lifetime value (500 customers, $20k annual contract value). And reducing churn in this example is saving just 5 customers a year. 

‍

Examples of Customer Signals‍

‍

Identifying, classifying, and escalating customer signals to the right people at the right time empowers companies with information and insights to preempt issues before they spiral and seize revenue opportunities in time to improve the bottom line. 

‍

For example, when a customer asks, “Can I have a copy of our contract?” in a support ticket, a signal is being sent. In a SaaS environment, the customer is likely signaling risk. Maybe they are evaluating a competitor. Perhaps there has been an executive change or a shift in priorities. Regardless, every SaaS leader will agree that this signal needs to be escalated so action can be taken. 

‍

Below are a few other examples of customer signals. This is not an exhaustive list; every company will vary on what is essential. An interesting exercise is to sit down and list out the signals that your teams should be watching for. The output of this exercise can be used to improve operations, user experience, training workflows, and more.

Customer signals help us understand our customers better than surveys and sentiment alone. By defining and leveraging signals at scale, we can clearly understand if our products are delivering the value promised at the time of the sale. We can also better understand if our customers are willing to grow with us or are growing away from us. 

‍

“B2B companies historically lag behind their B2C counterparts in adopting and deploying commercial analytics, but the ones who engage with the tools already outperform their peers; their return on sales are up to five percentage points higher than that of their counterparts.” McKinsey

‍

New analytics tools like Customer Intelligence platforms reveal opportunities for cross-functional collaborations. And the insights often have significant implications for non-sales teams. Rapid advancements in technology, especially AI, are making it easier to help brands quickly and responsibly use data to understand customer behaviors and predict customer needs. We can better anticipate future decisions when we discover new patterns and insights in our data. Ultimately, going beyond surveys and sentiment by leveraging customer signals presents opportunities and incentives to deliver better service and find new ways to grow.

‍

‍

We’re in the decade of data. Data products like Snowflake, AWS, Azure, and Google Cloud have created more market cap than any other segment of SaaS in the last five years. Unfortunately, the ripple effects have been slow to reach every business unit, especially customer experience teams — couple this with macroeconomic malaise, layoffs, and customers’ changing needs. The demand for deeper customer insights will be a top priority for B2B SaaS companies in 2023.

‍

Dirty data continues to be a drag.

‍

Let’s face it; when you don’t believe in the data, you quickly lose faith and are often forced to rely on your intuition to make decisions. The old expression “garbage in, garbage out” was coined nearly 50 years ago. However, we still struggle with data quality or what we refer to as dirty data. Dirty data is inaccurate, incomplete, or inconsistent data sets. 

‍

So what stands in the way of gaining more timely and accurate customer insights? You guessed it — dirty data. Brian Hall, President & Founder of Carema Consulting, states, “Dirty customer data is the biggest threat to successfully realizing a land & expand strategy.” Here’s how dirty data plays out for many customer experience teams. The current customer health score shows the customer is green. Usage levels are normal. The account manager had no risks flagged, but there’s no connection to the ticketing system to let the AM know there has been a spike in tickets over the past two weeks. Disconnected data. Unmatched data. Dirty data makes it nearly impossible for many teams to identify the early warning signs associated with risks. 

‍

Your customers aren’t going to tell you it’s about the data when they complain. Dirty data certainly isn’t going to show up in survey responses. But bogus data is the root cause of your customer problems. 

‍

In 2022, the team at Sturdy spoke with over 100 CX leaders and attended several CX-focused conferences. What we heard was consistent — teams don’t have the correct data to look through the windshield. Instead, we are still looking through the rearview mirror. Here are some of the most common challenges. Sound familiar? 

‍

1. The focus is on retention, but there’s a lack of available data to identify risks consistently.

2. Everyone wants higher unit margins, but most fail to employ automation effectively. 

3. More teams want to leverage customer data, but reliable sources are scarce.

‍

You probably saw plenty of 2022 predictions about sexier topics. “This is the year of digital transformation!” “The year of value creation!” 

While those things are essential, it’s just lip service without the right data. I predict that the data decade will continue roaring in 2023, fueled by the further adoption of data management solutions and the growth of Customer Intelligence Platforms. Such platforms will turn data into the insights teams need to create more long-lasting customer relationships. 

‍

Here are the top trends I am watching for in 2023. 

‍

Dirty customer data gets its day.

‍

Dirty customer data is the root cause of most customer-related issues. And to compound the pain, tech solutions that would typically solve data issues, like artificial intelligence and machine learning tools, require access to accurate, high-quality data. The old chicken and the egg problem. 

‍

This year we’ll see more B2B SaaS companies taking a more strategic and systematic approach to customer data management. While it will primarily be a people and process challenge, more customer intelligence companies will enter this space, especially as the need for tools to provide solid data quality and analytics solutions continues to grow.

‍

Customer data democratization grows. 

‍

More businesses will adopt customer intelligence solutions to provide self-service-oriented insights across multiple business units. The trend here will take the pressure off traditionally under-resourced CX leaders to be the clearinghouses for all post-sale customer-related data. 

‍

This year BI and CX ops teams will focus on building new analytical frameworks with corresponding data. Product teams will start to have access to the unbiased, unabridged voice of the customer. Marketing teams will more intelligently identify customers willing to be priceless advocates.

‍

Data-driven insights overshadow surveys.

‍

More and more, a leading B2B CX strategy is to use data to discover what customers are doing and saying every day instead of focusing on surveys. Like many metrics we use today, interviews and surveys rely on customers’ recollections, which are always backward-looking and biased. Data-driven insights provide an impartial lens into customers’ actual words in near real-time. 

‍

I predict more leaders will dispense with the survey charades. We’ll see more teams begin to rely on insights derived from customer ecosystem data to identify risks and opportunities to improve the customer experience. 

‍

The activation of AI-fueled automation.

‍

Automation is the future for many business units. As more mundane tasks are automated by machine learning and AI, humans have increasingly more time to devote to developing relationships with customers. AI can also simplify data unification by providing more streamlined, intelligent processing. 

‍

With its ability to comb through big data sets like customer emails and tickets at faster speeds, AI-forward Customer Intelligence Solutions will enable leaders to service the one-to-many segments successfully. Brian Hall exclaims, “email and tickets represent a largely untapped treasure trove of customer insights for B2B SaaS companies. Those companies that leverage these insights have the best chance to consistently grow customer lifetime value.”

‍

Get ready to leave dirty data in the dust. 

‍

Over the last few years, we have seen some paradigm-shifting evolutions in data technology. The near ubiquity of unified data management systems (data cloud products as described above) has made it possible for many of us to collect, combine and consume new data sets. 

‍

Businesses will put a dent in dirty data this year, driven by AI-fueled innovation. Here is how:

• More business units will benefit from customer intelligence solutions that provide democratized customer insights. 

• The unabridged, unsolicited voice of the customer will ring with accuracy, replacing the stagnant straw polls and surveys that teams have long relied on. 

• AI will surface contextual data in real time, making automation a reality for scaled customer experience teams. 

‍

Data-driven power shifts are redefining customer experience. It doesn’t matter if your business has bought into them yet, the shifts are happening either way. 2023 is the year that many CX leaders will start to leave dirty data in the dust.

‍

‍

Valuize's Chief Client Officer, Emily Ryan, invited our very own Joel Passen to discuss data hiding in plain sight. Hosted on LinkedIn live, the Valuize team has been kind enough to share this excellent content with us.

Hosted by: Emily Ryan, Chief Customer Officer at Valuize

Initially hosted on LinkedIn Live

‍

Interview Annotations

‍

1:15 | Introduction

2:20 | Icebreaker

4:10 | When I say customer success operations, what's the first thing that comes to mind for you?

5:40 | The silo-effect

9:41 | Getting a seat at the table

11:10 | Maximize data

14:00 | The richest source of customer feedback

20:20 | Product usage data

21:21 | Telemetry data + qualitative data = insights hiding in plain sight

22:08 | Rarely are you broken up with in the moment that the breakup happens

23:32 | Taking out the guesswork

24:36 | Structuring data in a consistent and repeatable way

26:30 | We're all on the same team

‍

0:00:08.8 S1: Hi, friends. Welcome back. I feel like it's been a million years since you’ve seen us on CS Operations. See, I don't even remember the title. A conversation with Emily Ryan. I'm Emily Ryan, and I'm so excited to have the opportunity as we have all year, this is actually coming up on a year of episodes, to have the opportunity to nerd out with some of my favorite people talking about one of my favorite topics, CS Strategy and Operations. This LinkedIn Live series aims to help define and defend investment in this critical organization, provide tips and tricks for designing a strategy to scale, and provide subject matter expertise to support this awesome new field. Each session will pose a different topic to a unique guest to help you get the most out of your time with us. If you have any questions or would like to connect with us or with each other, please feel free to engage via the comments. We'll try to leave some time to address questions during the session, but if we don't get to your question today, be on the lookout for future conversations, or you can visit our website to engage with our resources.

‍

0:01:11.0 S1: Let's change the way people work together. I'm so excited to have Joel Passen, and I actually didn't actually ask you how you say your last name, so my apologies.

‍

0:01:21.7 S1: Got it. You nailed it. Cool. We're good. Sweet. He is a SaaS entrepreneur, an investor, and an advisor. He is also the founder of Sturdy, a customer intelligence solution that empowers businesses to leverage unstructured customer feedback from every channel, like email, tickets, chats, meetings, and more. Sturdy uses AI and natural language processing to identify opportunities, reduce risks, and create more durable and profitable customer relationships at scale. I know durable is a huge word coming into the ecosystem right now, macro economy being what it is, but thank you, Joel, for joining me. Welcome. Thanks for having me. I'm glad to be here. Yeah, it's going to be fun. We always start with an icebreaker. Since we in the States, most states anyway, recently saw daylight savings end, it might be the last time that that happens depending on how things go in our government, but does daylight savings time mess with you? Relatedly, what is your favorite time of the day and why?

‍

0:02:38.6 S1: I'm going to answer this in reverse, actually. Favorite time of the day is I'm a morning person. I get to work out and it's quiet in my house. Also, I think I think a little bit better in the morning. This is probably good that this event is in the morning. Morning for me, I'm on the West Coast. In terms of daylight savings messing with me, it does because I have small roommates, a six-year-old roommate and an eight-year-old roommate. They don't necessarily understand, their biological clocks don't necessarily understand daylight savings. It messes with me because it messes with them. Right. Yeah. I have furry roommates who are also like, why have not my meals appeared yet?

‍

0:03:24.2 S2: Yeah. It's the same thing. Mine aren't that furry, but it's kind of same jam.

‍

0:03:30.5 S1: Yeah, exactly. Yeah. I'm also a morning person, which comes in handy these days. I'm actually doing an MBA at the same time. I wake up super early to do homework, which sounds really exciting. Well, you know how to live. I mean, that's amazing. Dream life. Yeah. Learning about applied financial management this term. Go me. Awesome. Well, the second question that we always ask is when I say customer success operations, what's the first thing that comes to mind for you?

‍

0:04:06.1 S1: I think about Rev Ops. I kind of blend all these things together. I'll tell you a quick story and the reason I mentioned this. First of all, I'll tell you, not to ingratiate you or the audience, but I think CS Ops is insanely important. I was at an event recently and somebody asked me a question like, if you're going to hire, you had $3 million in ARR and you had to assemble your team and turn in your budget. We were talking about budgeting. I'm like, what would be your, how would you backtrack the math? And I'm like, okay, first, first, good. You're talking about math. Math is good. And Ops sort of plays into that. And what I told them is I'm like, okay, I would try to figure out some sort of tech touch. Obviously I would have my head count resources. I'd be planning for some attrition in that. But I would talk a lot about in my budget, adding a CS operations or data analyst. And I would also, I think enablement CS enablement is also really, really important. And I think those are often overlooked as early hires. CS Ops, it's important to me.

‍

0:05:16.3 S2: I would hire that person really early in my life cycle.

‍

0:05:19.7 S1: Yeah. And, and to your rev ops point, right? I mean, we, we see sales ops come into play pretty early. We see marketing ops come into play reasonably early to get that scale, to get those touch points. But yeah, to your point, CS ops is just forgotten for a really long time.

‍

0:05:39.7 S1: I also think that there's a little bit of the silo effect too. I mean, you know, we're, we're talking about, we're talking about data that can impact, you know, CX CS and, you know, other folks, we're talking about customer generated data, right? And, and, and the topic of this, and I think it's really important to think about like, you can hire CS ops people. I would really want them tightly aligned to the rev ops org and the business or, you know, the business systems org. I think there are more and more product operations people coming up, but all of this layer needs to sort of funnel into a consistency. And I think that's one of the big opportunities that the industry has. And I think that CS ops people sometimes are on their own Island. And I don't necessarily think that's good because the data that they play with and the data that they're making sense out of can be used by all these other teams and the teams that are using, you know, conversely, like the rev ops and product ops, most people all need to use the same data sets to create new analytical frameworks.

‍

0:06:42.4 S2: So I'd like to see them less siloed. So I might say rev ops would be the first thing I think about because I think it's all kind of revenue operations. I think the next thing I'd say is like, keep them off their Island or out of a cave and put them more in the mainstream.

‍

0:06:57.5 S1: Yeah. Yeah. That's interesting. I don't know if it's an Island or a cave. I feel like, I feel like it might be an Island and it's like just far enough away that you can see other people. You can't actually talk to them. Yeah. They're kind of like, what does that person on that Island do over there? Oh, that's CS ops. I'm like, that's their little, why don't they have a lot of, there's not a lot of area on their Island.

‍

0:07:18.5 S1: You know, we need to also give them a nicer things. I think one of the things that I find in CS ops and you talk to them and these folks, these professionals, it's like, you know, how do you beg, but you know, what do you, how do you get resources? You know, do you have access to Tableau? Are you working or Domo or whatever you're using? And like, how do you, and they're kind of siloed. They're like, Oh, well I'm in our CSP and our CRM. Right. You're like, well, what, there's a broader subset of tools that in tooling that you should have. Well, we don't have the resources for that. Right. And it's the same thing by the way, in HR ops, I come out of the HR tech space, you hear it all the time, like TA ops, HR ops. They're kind of on their own little iceberg Islands in an orbit too. And they kind of look, their islands look and feel like the CS ops islands. Right. Yeah. Just like a person. And sometimes even part of a person.

‍

0:08:10.4 S2: Yeah. Yeah. They've got one or, and they're kind of like trying to find food.

‍

0:08:13.9 S1: Yeah. I, well, and the having nice things too. I think that that's, you know, that's one thing that, that we've spoken about a number of times on the Valuize side is as a CS operations person, learning how to speak in money because the value that you bring to your organization, if you can highlight that in real revenue and profitability terms, now folks are listening, but I think that it's taken a while for, for operations professionals to really get in that head space. Yeah.

‍

0:08:47.5 S1: I would, I would actually add to that and say, as a, maybe, you know, I've been sort of listening at, on the conference circuit for two years and attending stuff like this and like kind of showing up in the conversation and just to listen and absorb and learn more and more. I've been more of a CRO person. I've owned CS twice. And I've always had really been fortunate to have good chief customer officer, VP of CS, CX. I've always had customer operations by the way, early on operations really important. But to your point, like I think one of the things that I've heard a lot of on the circuit to, I think a greater extent, I heard it again this year, it was like, Oh, getting a seat at the table. And there was like, there's all this kind of like talk about getting to see the table. By the way, I've heard all of this in the HR Tech years and years ago, like how does HR get a seat at the table? I'm like, it's our most important asset to have our employees first. And you're like, yeah, it's really interesting how aligned these spaces are because HR talks about the employees getting, you know, if you talk to a CEO, like, and say, what's your most important asset?

‍

0:09:53.6 S2: They're like, Oh, our people. Right. And behind closed doors, they might say our cap structure, right. And I think in customer success, by the way, they're like, we want to see to the table and you go to the CEO, like what's your most important constituencies of people? And of course our employees and our customers, you know, they're equal. But yet I think one of the things that people forget about is thats lip service to a certain extent. And that if you want to see to the table, you got to talk in revenue speak because CROs and the product people, you know, the product people kind of get a pass to no fault of their own. They get, they get nice things. Sales teams get nice things because they own a huge number and somebody thinks they need nice things to make that number. But I think that's trend. We might be moving the needle for CS folks, but I think I really encourage people to think about like, yeah, when you speak in revenue, you wield power. That gets you a seat at the table immediately.

‍

0:10:49.2 S1: Exactly. Exactly. Yeah. So digging into like how, right? So, I mean, early in my software career, I had the opportunity to dive into customer success operations even before it really formally existed as such. And one of the first things I learned in that experience was to maximize data, to gain any level of consistency against delivery. Today, over a decade later, we still come across clients at Valuize who insist that they don't have data. And usually it's because they're focused on like product telemetry specifically, but I know Sturdy aims to debunk this myth by leaning into the rich data sets that commonly go unnoticed and aren't tapped into. What are your thoughts about how companies really, especially B2B, but you can talk about any company, can lean into that rich vein of data and what is this data and why is it important?

‍

0:11:52.7 S1: Well, I think it'd start with a stat. So we've had the really good fortune at Sturdy to analyze 55 million conversations collectively. And these can be things from call transcripts to tickets to in-app chats to customer email. And so when companies, to your point, when they talk about, oh, we just don't have any data or our data is a mess because you hear those two things in, oh, not quite ready for that because our data is a mess. And my answer to them is the first thing is I'm like, you have an enormous, enormous amount of language, like your language and feedback, and it's all stuck in email in a variety of silos. And so you have the data and you've been collecting the data for a very long time. And there's trends in that data. If you just think about the single channel in email, it's amazing. And yes, it is an enormous rat's nest of unstructured data. But the cool thing is there are companies and Sturdy is not the only one. There are others that are starting to make sense out of that and being able to distill that information from these silos, ingest it and restructure it in a very consistent, accurate way.

‍

0:13:01.2 S1: So the, we don't have any data is a tough one these days because you just have a ton of ticketing data. I mean, the backend of your Gong calls or your Zoom calls with your customers, enormously valuable data. So it might not be what you would think of your data, Emily, in the traditional sense, like how many emails have we sent? How many times have we engaged the customer, which is really important stuff, but we all, you know, that's the kind of stuff we probably should have, but that's all telemetry based numbers that we look at in our rears. So, yeah, there's by the way, you know how many, you know, I'll put you on the spot here. You might know the answer to this. I feel like I've switched the thing you're supposed to. It's a dialogue we can talk.

‍

0:13:46.7 S2: Okay, cool. If you don't, I have the answer. So if you don't want the answer, how many, so across B2B SaaS companies, $50 million in revenue or higher, how much do you think in terms of all the channels of communication with customers these days, minus in person, because that's impossible to track unless the calls are recorded. What do you think the richest source of feedback and customer feedback or insights is derived from what channel of communication?

‍

0:14:13.8 S1: Like where is it derived from today? Yeah.

‍

0:14:17.0 S2: Like what, where does the, where does the potential lie? What is the, what, where do you think the treasure trove is?

‍

0:14:23.1 S1: Gotcha. I would say it's just all of the back and forth engagement. So anytime your customer responds to something or reaches out, so I'm going to cheat and say any inbound email from your customer and more specifically support tickets.

‍

0:14:45.2 S2: Yeah. You're right. What we find is over 60% of the back and forth communication between customers and I'm talking users and customers, not just your key stakeholders, over 60% of it is an email across on an average nine inboxes. Yep. So if you think about it, yeah, we don't have the data. You can't say you don't have that. You have a lot of data just unfortunately stuck in all these little pits, these little tar pits that you can't get things out of, you know, conveniently. But there's a lot of really, you know, customers in an, you know, if you look at emails and you analyze emails, it's really like an unabridged, unbiased voice of the customer. They are telling you the answers. Yes. It's just really hard to get at.

‍

0:15:27.9 S1: Right. Well, and to your point, like the nine, I mean, there are nine silos into which those emails dump and there's overlap with different emails. So let me see. I would imagine that's, probably some of that goes directly to your sales person because there's never been a severed relationship there. Not that that relationship should be severed, but it should be re refocused. Right. It's your, whoever your technical kind of onboarding first person that talks to your customers inbox or group inbox, it's your CSM or CSM equivalent. So if you have a pool model or digital model, it's your support, ecosystem. So all of the tickets and all of the rich things there, I would imagine it's any engagement with your community or your marketing, ecosystem. Let's see, that's, that's half.

‍

0:16:23.3 S2: I'll give you, you're, you're an expert, so you're, but hold on, hold on. Yeah. Billing. Oh yes. So when you, when you build accounting, accounting is huge and it's, by the way, it's very literal. Those are very binary exchanges.

‍

0:16:38.2 S1: Can I have a copy of our contract?

‍

0:16:39.7 S1: When is the renewal of our contract? Yes. It's, it's November 15th. When's our auto renew trigger. Right. So, and possibly if you've got, you know, similar like that, linking that information with a support ticket, I'm cheating cause you told me this, but I'm linking that information with a support ticket that says, can you point me to the place where I can extract data from our system? Now you've got turn. Yeah. Well, you've got a couple of different vectors to say like, Hey, this is an issue. By the way, if you get a support ticket, it's kind of interesting for like when is our renewal date and somebody might go into Salesforce and be like, and by the way, in, in trying to do the right thing, you know, in a timely manner to provide an excellent level of service. Hey Emily, it's November 15th. Thank you so much. Is there anything I can help you with? No, there's not. Emily Ryan says, okay, case shut right. I'm moving on. If you blend all that language together or if those things get, escalated to somebody that's like, hold on a second, let's have a conversation with these people.

‍

0:17:42.0 S1: They're asking a question that, you know, 65% of the time leads to a cancellation in the next 12 months. Right. So we need to get this to somebody that has the aptitude, you know, probably an account manager or a CS person that can have a conversation with these people and better understand why they're asking the question. Can you save a couple of customers a year doing that? Yeah. That's using data hiding in plain sight to actually lift net retention or you're just kind of stem this, you know, stem off cancellations. Right. I mean, that's what we're talking about when we're using qualitative data to do this stuff. It's the, they're there, the, the signs, the insights are sitting on there. The other ones, by the way, so billing program management, people that are touching integrations or partnership types things where you're engaging or, you know, maybe you're upset, maybe you're getting upsold by account management. So, anywhere from like seven to 12, right. Seven to twelve touch points at any given time at larger enterprises. It's, it's vast, even bigger, could be marketing, could be advocacy groups, that actually get insights from customers where they're like, I can't give you a customer testimonial right now.

‍

0:18:47.6 S1: We'd love to, but we have this issue. So what does a customer marketing person do? Like they try to solve that. Do they escalate it? Do they have to do data entry somewhere? I mean, there's some really murky things that happen to even with people that are well-trained and have the best interests. Exactly. Exactly. Well, and you know, this is another reason why we, we try to help our, our clients with, with whatever system they have starting to make sure that you are viewing the customer with the same lens. We see a lot of folks silo internally, the customer's information and data set by internal team members. So my CSM has of you, my salesperson has of you, my technical account manager has of you and the views are slightly different. And so one of the things that we do is try to crack that open and even extend it. So not only is your whole post-sale customer team looking at the same set of customer information, but we're making sure that support has a view into that, that professional services has a view into that, et cetera. and it's, this is the same type of motion.

‍

0:19:53.9 S1: It's like these, not just the customer information, but the data around all of those interactions. And to your earlier point, it's not, it's not just about quantitative interactions. How many times or, you know, how many times did my customer user open or click on like that's important data probably, but then what, so what, what else happened?

‍

0:20:20.9 S1: I also think that product usage data, if you're in like the, we have payroll providers as customers, you don't just stop doing payroll or tail off and doing payroll in January 1st when your first payroll starts with your new customer. Yeah. Your usage goes from like a hundred percent to nothing that usage doesn't tell that story. So some of the things that we incorporate, I know that, Valuize does good work with customers around helping them sort of create, maybe more holistic health scoring. And I read a lot, you know, like part of the reason that I think I'm on this, with you today is like, you talked about data centricity and I was like, yeah, that's the, that's the, you know, and some of the value wise content, which I think is really quality. And I've mentioned this to your team before, really quality content for people that are looking to get information. You guys write a bunch of, but data centricity, which isn't a light reading topic, but it's really, really important. So, I mean, I think that's what you're trying to get at without beating your own drum, but it's really, really important.

‍

0:21:21.4 S2: So yes, telemetry data combined with qualitative data is sort of like, if you take the data that's been hiding in plain sight, the stuff that you're collecting, you have reams up, you just need to make actionable and you combine it with some of this telemetry based data. It accelerates or, or, I think enhances the story. Like you kind of get to the, what we're all looking for is like, this is happening. Oh my gosh. Like, and then you have to say why, and someone can be like, this is what we've seen. This is a lot of the topics in their conversations go around these feature requests. And one of the things we talk a lot about is like cancellations. They don't happen in a vacuum. No, it is a compilation of lots of things with all of these different actors in all these different silos. And this is part of the reason that's really hard to get in front of cancellations. It's like it's all over the place and it's death by a thousand cuts.

‍

0:22:08.5 S1: Yep. Yep. And just like any, any relationship, you know, rarely are you broken up with in the moment that the breakup happens, you've been broken up with mentally long ago, right? Yeah. Well, yeah, yes. And you know what we're talking about, we're talking about investing in relationships. So, I mean, that metaphor goes a really long way. And when I, I mean, I'm sure you get out and talk to your customers. I get out and talk to mine. It's like, yeah. I mean, think about your own relationships. There are fractures and fissures. And by the way, sometimes, and to this point, sometimes you have really hard conversations in a relationship, a personal relationship, and it makes you stronger with that person because you get to trust. And I think that confronting these fissures and fractures and client relationships head on and honestly with, with high intellectual honesty, right. Sometimes can create a really strong partnership with that customer. They're going to renewal infinitely, right? They love you. You've provided value. Listen to them and listening to their customers, like kind of how this all starts, because that's kind of key to a relationship. So absolutely. And you know, your, your, the work that you're, you and your team are doing helps enlighten your internal teams broadly about those things that your customer is telling you, right?

‍

0:23:26.3 S1: So you can have, it's, it takes the bias out of things or the guesswork like, Hey Emily, how is a XYZ customer?

‍

0:23:32.6 S1: Are they green, yellow or red? Well, I think, I feel like, I feel like that's how a lot of these conversations start where I'd like to say, I feel like they're a little bit of a yellow because we don't have this particular feature and the buyer, we lost our executive sponsor and the new executive sponsor has bought ADP or workday or whatever the competing product is before. So I think we have a little bit of risk. That's what I know. Now, if I'm a leader and I get that download and I'm like, okay, we need to fly to Topeka and go talk to these people and go, that's a trip that I'm going to budget. Like we need to get in front of these. What's their error? Oh, it's this. Yeah. We should get in front of those folks. Right. Yep. No, it's true. And I think, you know, one of the things that we were talking about the other day was just the kind of, you know, we talked about rev ops, the sales and marketing components of that really have learned how to get a lot of data and structure that data in a really consistent, repeatable way.

‍

0:24:36.2 S1: And customer success and post sales in general seem to continue to lag behind when it comes to truly understanding customers through data. Just as kind of our final moment here, what's your perspective when it comes to this like dichotomy within SaaS businesses and how can companies strive to overcome that?

‍

0:24:58.8 S1: So the first thing that I would say just with few words is that it's a maturity issue. You know, CS ops is relatively new compared to revenue operations, which is I think fairly stable. I mean, any business with over, I don't know, what do you think? I'm like $5 million in ARR? You're going to have a full-time rev ops person or at least somebody who's aspiring to do that role, if not augmented with some sort of consulting, cause you're going to need it. And as the motions grow, it just gets more, you know, those teams bloom. There's a whole industry around it. There are platforms, all kinds of stuff. It's mature. I think in CS it's just not mature. And I think the second point is, you know, how do we get people there? I think that like anything else, like how, how does a good sales person or account manager learn? They learn through osmosis through shadowing and being mentored by someone else. So I think CS ops and it comes full circle. Like you asked me what I think of CS ops. I'm like rev ops because I want my CS people, my CS team to be lockstep with the revenue motions with rev ops so that we have to pair them together and that'll increase the maturity on our mathy and data side of the world in customer success or post sales motions.

‍

0:26:10.9 S2: Yeah.

‍

0:26:11.4 S1: Yeah.

‍

0:26:11.7 S1: Like we have to, we have to get closer by the way. They're too, these teams are too segmented. They're too segmented. Like we're all in the revenue game and we're all in the delighting the customer game, whether it's product sales and customer success, we are all on the same team. And that I think sometimes is lost in fiefdom building. It really is. Yeah. Yep. That's a, that's a, that's a nice little tagline into, I will, I will shamelessly pitch our value experience framework release drives to break down those silos and help teams work together towards a common discipline so that, so that we're really driving towards net dollar retention and delight is a core part of that.

‍

0:26:53.4 S1: Well, let me know if you guys take the show on the road to Topeka. I'm available. They have planes. Sounds good. Sounds good. I feel like it's starting to get to the wrong season to be in Topeka, but It is actually, I've never been to Topeka this time of year, but I would imagine that we probably want to wait until the spring.

‍

0:27:11.4 S2: No offense to Topeka constituents, but yeah. Yeah.

‍

0:27:14.6 S2: I know that, you know, Kansas is a, is a neighbor of ours and man, do they get the weather that just comes right off, but skips Denver and then just goes straight to Kansas. So it's wait until spring. Well, as usual, this time just completely flew. Thank you, Joel. And thank you everyone for joining the discussion today to uncover data in your blind spots and maximize customer insights. Let's change the way people work together. Let's do this again too. Let's do it again.

‍

0:27:49.5 S1: Right. Let's, we have so much to talk about. We can keep talking later. Thank you. Thanks for having me. My pleasure.

‍

‍

Since starting Sturdy, we have learned that about 50% of support tickets and 15% of emails contain a roadmap-informing data point.

‍

I have worked on the product side of software for about 20 years, and the most common question from management is, “What are we building next?”. It is a question that I ask myself almost every day.

‍

Answering “what to build next?” isn’t always easy, but explaining “why we are building this next?” never is. 

‍

(Inevitably, engineering will want one thing, support another, and sales yet a third. But I digress.)

We were not venture-funded at Newton Software, so building the wrong feature could have killed us. We took these decisions very seriously.

‍

We had 3 weekly meetings to inform our “why build it?” decisions. Our Support Team leaders were in charge of mining tickets for the most common bugs, “how do I do this?” items and feature requests. Our Customer Success leadership was responsible for capturing similar data, mainly found in email. And finally, there was a third meeting with Sales leadership, where they informed us of the features they need to close more deals. 

‍

In other words, we manually harvested data from multiple data silos and teams to inform product development decisions. This data was in support tickets, emails, chats, and phone calls. Someone would need to manually record data in something like JIRA or Salesforce to even have it. If they didn’t record it, we didn’t get it.

‍

Effectively capturing data to inform product roadmaps is probably the most important thing a software company can do. As product planners, we rely almost entirely on other teams to manually source, process, and organize this data. The teams have other jobs though…

‍

After Newton was purchased and we were in a larger organization, it became apparent that manually converting conversations into data was too time-consuming and expensive. It didn’t happen. As a result, we had almost no data informing our product decisions. 

That’s why (after exiting Newton) our “What do we build next?” question was answered with, “Let’s build something that turns all of our customer feedback, tickets, conversations, and emails into some real data!”

‍

Every time a customer contacts your company, they want you to listen. You want to listen. Take this simple challenge: count the number of new support tickets you got last month and cross reference JIRA. Did 50% of those tickets turn into data? Now try the same thing with email. We know it’s not easy.

‍

By turning all of this feedback and information into data, product planners can access and employ the voice of the customer to make informed product decisions. If making more informed product decisions is essential to you, give Sturdy a look. 

‍

Don’t hesitate to contact me at steve@sturdy.ai if you have any questions or comments.

‍

Customer attrition is a certainty for any SaaS company. The simple truth is that you will lose customers over time. Sometimes this attrition is out of your hands. However, at other times, you can directly impact whether or not it occurs. This post will explain customer attrition and how you can proactively mitigate it.

‍

What is customer attrition?

‍

Customer attrition is the natural process of customers leaving a company or product for one (or more) reasons. Customer attrition can be broken down into two categories: voluntary and involuntary attrition. 

‍

Voluntary attrition is when the customer chooses to end their subscription. A customer may decide to leave for various reasons. Perhaps that customer is dissatisfied with your service and has moved on to one of your competitors. Maybe they no longer require the service you're offering.

‍

Involuntary attrition is when a customer fails to make a payment, leading to their subscription being canceled. Maybe your customer has been acquired. Alternatively, your customer may have stopped paying bills and is on the verge of going out of business. Involuntary attrition is arguably more frustrating since there's little you can do to prevent it. For that reason, SaaS companies tend to focus on managing voluntary attrition.

‍

Whatever the reason, SaaS business leaders should not take customer attrition lightly. Why? Because customer attrition impacts the bottom line. According to Invesp, it can cost companies up to five times more to acquire a new customer than to retain an existing one. Moreover, Totango's Guy Nirpaz states, "70–95% of SaaS revenue comes from retention and expansion of existing customers." For SaaS companies, net dollar retention, or NDR, is the lifeblood of the business.

‍

NDR provides a revenue-based view of customer retention. NDR is increasingly important as you scale from small to medium-sized businesses and beyond. For example, a $5MM company that churns 20% can replace that $1MM with net new business when it's growing by +50% a year. But when a $30MM business needs to return $6MM due to customer attrition, this becomes significantly difficult if the growth rate slows.

‍

It should go without saying that improving customer attrition rates should be a top priority for SaaS business leaders. But how? Where should they start? Here are some tips.

‍

Six strategies to combat customer attrition

‍

1. Listen to customer feedback and act on it.

‍

Listening to your customers is more complicated than it sounds. And yet, customer feedback is the single most crucial element in reducing customer attrition. SaaS companies collect daily customer information but need to convert it into valuable, actionable data. Let's face it, NPS and CSAT scores hardly tell the whole story. Usage Data is excellent but can be misleading without context. Survey data is unreliable. That's where Customer Intelligence (CI) tools like Sturdy come in. Customer Intelligence is collecting and analyzing key customer-generated data to glean crucial insights such as risks, trends, and opportunities—all of which help drive revenue. CI is critical in unlocking customer insights, often using advanced data sciences like artificial intelligence, machine learning, and natural language processing. CI allows you to distill the insights from the noise so your team can take the following best action. Without CI, you're only half-listening to your customers.

‍

2. Make sure customers are getting value.

‍

One way to keep your customers is to make sure they understand the value they're getting. You can do this through effective onboarding and by setting expectations appropriately. Another way to ensure value is to go above and beyond expectations. This could mean offering extra features or benefits at no additional cost. It could mean providing superior customer service or simply doing whatever you can to ensure your customers are happy. By focusing on value and exceeding expectations, you can ensure your customers are satisfied with their purchase and more likely to stick around.

‍

3. Keep communication open and transparent.

‍

Keeping communication open and transparent with customers is essential for success. Through transparent communication, businesses can ensure customer attrition rates remain low, and customer satisfaction remains high. A ZDNet study concluded that "Organizations can reap rewards from being transparent. Nine out of 10 people (89%) said a business can regain their trust if it admits to a mistake and is transparent about the steps it will take to resolve the issue. A similar ratio (85%) are more likely to stick with them during crises." 

‍

4. Maintain product-market fit.

‍

Product-market fit describes your product's ability to deliver value to customers. If your customers stay with you and keep paying their subscriptions, you're in a good place. However, product-market fit is by no means the end of the line. It isn't a box you can check off and then forget about. To succeed, your product needs to continuously evolve to meet customers' needs.

‍

Early on, your top priority is feedback when you are working towards validating product-market fit. While collecting quantitative data like engagement metrics and survey scores is helpful, capturing your customer's unbiased, unabridged, and unsolicited voice is the most important thing to do. This is only possible with the help of a Customer Intelligence platform.

‍

5. Offer customer incentives and loyalty programs.

‍

We've previously explained why incentive programs are essential and provided five steps to build a successful one at your company. Customers loyal to a company are more likely to recommend the company to friends and family. Customer incentives and loyalty programs can be a great way to show customers that you appreciate their business. They can also be a great way to encourage customers to continue doing business with you.

‍

6. Provide a reliable and proactive customer experience

‍

Customer attrition is a "rearview mirror" metric. Traditional reports and surveys capture what's happened in the past. With Customer Intelligence, you have valuable insights at your fingertips to look forward through the "windshield" and to see around the corners along the way.

‍

Our research shows that 65% of accounts with an executive change churn within 12 months. Teams that act on executive change signals within the first 48 hours of discovery have a 33% higher likelihood of renewal.

‍

Using innovative data sciences like AI, ML, NLP, and deep learning, Sturdy analyzes every email, support ticket, chat, and more for specific insights. This empowers your teams to focus on relationships that drive revenue. 

‍

Conclusion

‍

By understanding customer attrition, SaaS business leaders can proactively address customer dissatisfaction before it becomes an issue and continually improve customer loyalty and value. This is a critical factor in any business's success, so it should be noticed. By listening to customer feedback and implementing strategies that keep customers engaged and satisfied, companies can ensure customer attrition rates remain low, and their bottom line remains healthy.

‍

‍

Few things are more critical to the success of a business than developing customer advocates. Every brand wants to make its customers happy. In SaaS, even minor improvements in customer experience lead to more significant gains in customer retention. Considerable increases in customer engagement significantly boost retention revenue. According to Guy Nirpaz at Totango, “70–95% of SaaS revenue comes from retention and expansion of existing customers.” You heard that right — yes, this surpasses net new revenue figures. The initial sale generates as little as 5% of SaaS revenue. As the SaaS economy has matured, we have finally realized that replacing churn with new acquisitions becomes increasingly tricky, especially at scale. It suffices to say that in the world of SaaS, keeping your customers has become the top priority. 

What are customer incentives? 

According to our friends at Paddle, “Customer incentives are rewards granted to customers for engaging in behavior that helps build the brand.” Think of customer incentives as bonuses or rewards given to customers for promoting the brands. For example, customers may receive additional credits if they promote your brand on social media. Or, maybe you’ll give them access to more advanced features. They can be revenue related, such as making a repeat purchase or upgrading an existing plan. They can also be action-oriented, like writing a testimonial, referring another customer, or participating in a webinar or a panel. 

B2B rewards and incentives are diverse, including product discounts, rebates, discounted or free products, features, early access to new functionality, charitable donations, and more. Compared to their B2C counterparts, B2B businesses tend to develop more personalized, long-term customer relationships. Therefore, it’s common for a B2B incentive program to be more personalized and designed explicitly for specific customer segments and cohorts. For example, a discount incentive can be offered to a company that allows the vendor to use its logo for marketing rights. Or, the vendor can provide early access to a new SKU for free or at a discounted price. 

B2B incentive programs are generally less transactional than B2C programs. Instead, B2B programs are focused on deepening existing relationships. Customers must view the program as somewhat personalized, and it needs to offer a clear benefit. 

Finally, one of the best incentives for engaged customers is simply communication. As with any relationship, communication is critical. Companies that regularly communicate with their customers show that they care about them and want to keep them up-to-date on the latest news and developments. This communication can take many forms, such as emails, newsletters, social media posts, or even phone calls. By staying in touch with their customers, companies can build strong relationships that will last for years. 

Now that you have a good pulse on brand-building B2B behaviors and how to incentive those behaviors, here are five steps you can take to build a successful customer incentive program, grow customer loyalty, and improve customer retention. 

5 Steps to build a successful program:

There is no shortage of ways to incentivize customers to build your brand and business. Be creative. The sky’s the limit as far as creativity is concerned. However, not all SaaS companies are alike; thus, creating a custom incentive program is essential for success. It’s not like the worst that can happen is you don’t have any takers. A poor incentive program can lead to far worse outcomes — even compliance and legal challenges if you aren’t careful. Follow the steps below to ensure your program hits all the right notes.

1. Listen to your customers

Understanding your customers and ideal customer profiles (ICPs) is the first step to creating a successful incentive program. To better understand your ICPs, you must listen deeply to what your customers say. The key here is to go beyond traditional tactics like NPS and CSAT surveys like NPS and CSAT. Nothing speaks louder than the unabridged, unbiased, unsolicited voice of your customer. The most competitive businesses analyze everyday customer conversations to distill thousands of data points a month and capture customer sentiment at scale. Taking that step can only be accomplished through a customer intelligence platform (CIP). 

2. Choose your goals

As we mentioned above, there is no shortage of brand-building behaviors. Is your program focused on generating more customer testimonials and case studies? Do you need more customer references? Or is the primary goal to increase expansion revenue? Different goals mean different programs. They also represent different audiences. You’re not going to ask a struggling customer who’s still onboarding to write a case study. Similarly, you’re not going to incentivize a customer who’s already planning on expanding their seat count to upgrade. 

3. Choose a test group

Testing your program on a smaller group minimizes risk. There are a couple of ways to choose your test group. Let’s say your program aims to generate 10 case studies for a new website landing page. Traditionally this has been a pretty manual task. First, you reach out to your customer success and account managers to ask which customers are “happy” or “most likely to write a testimonial?” Once you’ve chatted with a few colleagues, you can pull together your group. Alternatively, you can aggregate customers exuding positive sentiment in seconds with modern technology like a CIP. You will save yourself hours of work and have the underpinnings of a repeatable process and, ultimately, a healthier incentive program.

But what if your goal is to incentivize customers to upgrade? How do you know which customers are already planning on expanding their account versus those who are just ‘happy’? Positive sentiment doesn’t always infer expansion opportunity. Don’t spend hundreds or even thousands of dollars building a program to encourage those customers who are already about to expand. Spend that bandwidth and budget on happy customers who need an extra nudge. The issue for most is that they cannot tell the difference. Without a CIP, it’s nearly impossible to differentiate between those two test groups. With a CIP, however, you can define and segment those customers who are ‘happy’ from those that are ready for ‘expansion.’ 

4. Build a budget

Regardless of your program goal, it’s essential to map out a budget. This process can be relatively straightforward if your incentive and desired customer behavior are tied directly to revenue. For example, if I’m offering $10,000 of free products to generate $15,000 of repeat purchases, that’s $5,000 of net profit. Budgeting gets more complicated as the incentives and behaviors move away from simple transactions. Let’s say your incentive to generate 10 case studies is to provide early access to a new product offering. Determining the monetary value of a case study is difficult. Understanding what you want to charge for a new product offering is difficult without going through the proper motions. Still, getting everything down on paper and setting up a rough projection is critical. Ultimately, your budget should be a tool that determines whether or not what you’re giving away is less than what you’re getting in return. 

5. Analyze and iterate

Rarely does a customer incentive program knock it out of the park on the first go. There are often many moving parts, and it can be tricky to nail the incentives down on the first attempt. Depending on what brand behavior you’re seeking, these programs can take weeks, if not months, to conclude. Requesting 10 case studies is not going to be a quick turnaround. That said, it’s essential to track your program’s progress effectively. There is no shortage of project management tools to choose from these days. A CIP lets you quickly track leading indicators based on sentiment and insights. Regardless of how you’re monitoring success, keep an eye out for improvement opportunities.

Conclusion

Engaged customers are essential to the success of any B2B SaaS business. To properly engage with your customers, you must listen to your customers at scale. Only then can you offer them the right incentives at the right time to boost brand-building behaviors. Pair that with excellent customer service and regular communication, and you can build strong relationships that will last for years.  

‍

In any business, customer churn—or the percentage of customers who stop using your product or service—is inevitable. Cancellations happen. But that doesn't mean you should just roll over and accept it. There are things you can do to decrease customer churn and protect what is arguably the most important aspect of revenue — the longtail subscription revenue of your customer accounts. Let's take a look at the seven most effective strategies for decreasing customer churn.

1. Understand the most common reasons for customer churn.

The first step in dealing with customer churn is to diagnose why the customer is canceling in the first place. There could be any number of reasons, but consistent themes and topics will emerge with the analysis. Churn doesn't happen in a vacuum. It's a culmination of bug reports, feature requests, executive changes, response lags, unhappy sentiment, contract requests, renewal inquiries, and more.

If your team receives one or two pieces of feedback from a customer expressing frustration, it might not be the beginning of the end of the relationship. But, what about 10 times in 30 days? What if that customer is still in the onboarding phase of their journey? You'd want to know. And, more importantly, you’d want to take action to repair that relationship. 

2. Elevate customer engagement early on. 

Speaking of the onboarding phase, the first few weeks and months after a customer signs up for your product or service are crucial. This is when they get to know your product and develop a relationship with your team. Most importantly, this is when customers determine whether your service is really going to drive the value outlined in the sales process. If you can increase engagement during this period—through things like work sessions, listening workshops, self-service content, regular check-ins, etc.—you can set your customers up for success and decrease the likelihood that they'll churn later on.

3. Listen deeply to what customers are saying.

As previously mentioned, certain insights can be indicative of future churn—things like executive changes, contract requests, questions about the contract terms, unhappy sentiment, etc. By listening for these insights, you can proactively identify opportunities to guide the relationship early on and take steps to prevent them from turning into bigger issues down the road. Traditionally, for most B2B SaaS enterprises, this process hasn’t been scalable. Listening to your customers at scale is nearly impossible. Luckily, new developments in AI and machine learning have enabled customer intelligence platforms (CIPs) to analyze every email, support ticket, chat, and more for specific insights that empower your teams to focus on relationships that drive revenue. 

4. Take action on customer feedback quickly. 

If customers feel like their voices are being heard and that their feedback is being acted on, they're much more likely to stick around. As a baseline, make sure you have a system in place for collecting customer feedback (surveys, Net Promoter Score® emails, etc.) and that you're regularly reviewing that feedback to see what changes you can make to improve the customer experience. Additionally, take a step beyond soliciting feedback to ensure you’re capturing customer sentiment at scale. Nothing is more powerful than the unabridged, unbiased voice of the customer. As we mentioned earlier, that can only be accomplished at scale through a customer intelligence platform.  

5. Understand what features and services your customers want most. 

Find ways to add value for your customers—through things like upselling, cross-selling, or simply offering new features or services—you can reduce the likelihood of them canceling their subscription. At the end of the day, customers are either growing with you or away from you. Identifying trends in what your collective customer base asks for the most is a surefire way to keep your customers growing with you. Customers who feel like they're getting more bang for their buck are less likely to look elsewhere for a similar product or service staving off painful losses to competition.  

6. Provide the level of service you’d expect as a customer.

One of the best ways to prevent customers from churning is to provide them with the level of customer service you’d expect as a customer. If your customers feel like you're listening to their concerns, issues, and suggestions and that there is some actionable output, they’ll be less likely to look to a competing product that can provide them with what they need. The root of excellent customer service starts with simply listening and taking the next best action. Adopt the mantra of listening, acting, and improving. 

7. Seek to develop advocates, not just keep customers. 

Customer-obsessed companies don’t just service customers, their goal is to create advocates. Customer advocates are the ultimate customers. They serve as references and speak at industry events and webinars. They provide success stories, product reviews, and quotes for your marketing team. Developing advocates is about putting your customer first, and putting your customer first starts with listening at scale. It’s high time to start using all the feedback your customers give you daily to better understand their wants, needs, and issues so you and your teams can take the necessary action.  

For most B2B SaaS companies, customer churn is what we call the CODB — the cost of doing business. But the fact of the matter is that churn is a “rearview mirror” metric. Traditional telemetry-based reports and customer health scorecards capture what’s happened in the past, and most of the time, if you’re dealing with churn, you’re already too late. With CIPs, like Sturdy, you have valuable insights at your fingertips to look forward through the “windshield” and to see around the corners along the way. This allows you to detect and combat churn before it happens. It’s like a lead-gen for building more durable, profitable relationships. 

‍

Churn. We've all heard about it before, especially if you're building a SaaS business. There's no shortage of thought leaders who proclaim the all too simplistic mantra: "Decrease churn! And increase profits!"

Yet, for many, churn as a metric is confusing and ambiguous. For example, customer churn is different than revenue churn for example and there many ways to calculate churn leading to confusion across your company.

If you're tired of the over-reliance on churn, you're not alone. Analysts and investors have been increasingly skeptical of churn rate calculations for years.

“There are too many darn ways to calculate churn. That makes it ambiguous.” says, Dave Kellogg

So if churn isn't the magic pill many businesses want it to be, what should you be looking at?

It all starts with, net dollar retention.

‍

What is net dollar retention (NDR)? 

‍

Net dollar retention (NDR) aka net revenue retention (NRR) has emerged as one of the top SaaS metrics that matter and for good reason.

NDR takes into account upgrades, downgrades, and churn to quantify how much recurring revenue from current customers you retained across a defined period of time. Why focus on a single metric such as churn, that doesn't actually give you the complete picture of the health of your business?

While no one metric is going to transform your business overnight, net dollar retention does help answer two incredibly important questions for businesses (especially SaaS businesses) looking to grow.

Net dollar retention can help answer:

1. Is your product delivering the value promised during the sale? 
2. Are your customers growing with you or without you? 

Having answers to these two questions can dramatically improve your business across the board.

What makes net retention so powerful is that for most companies, it’s cheaper to sell to existing customers than to sell to new customers. This makes net retention the most cost-efficient way to accelerate revenue growth. Instead of investing tens of thousands of dollars in a new marketing campaign, you can strategically use net dollar retention to improve the qualities and services of customers who have already trusted you enough to make a purchase. Yes, acquiring new customers is part of the business game, but all too often businesses neglect one of the most important revenue streams that already exist: current customers.

‍

How to calculate net dollar retention

‍

If your NDR is over 100%, this means that an increase in revenue is attributable to your existing customers.

Here’s how to calculate NDR. 

(Starting MRR + expansion — downgrades — churn) / Starting MRR  = NDR

Here’s an example.

Let’s say you start the month at $100,000 in recurring revenue (MRR). Over the month it added $25,00 in expansion revenue, has $10,000 in downgrades and another $5000 in churn.

($100,000 + $25,000 — $10,000 — $5000)/$100,000 = 110% NDR.

Your MRR is $110,000 with an NDR of 110% This is good. Essentially, your upgrades / upsells lifted your revenue despite losses. 

Without understanding your net dollar retention rate, you might be under the impression your business is sinking without a solution in sight. But with the knowledge that current customers are helping keep your business afloat, you can continue to invest in your marketing and business strategy without making rash business decisions.

‍

What is a good net dollar retention (NDR) rate?

‍

A minimum NDR rate of 100% is considered good for SaaS businesses selling to the SMB market. Selling to smaller accounts naturally yields a lower NDR. SMB clients are less financially stable, ripe for acquisition, and have smaller budgets. 

An excellent enterprise NDR rate is 130%. As with many SaaS metrics, there are other things to consider. For example, Workday’s NDR is 100% but gross retention is 95%. Either Workday is very good at selling the “whole” deal or their product footprint presents limitations. 

Here are some examples of net dollar retention rates for some interesting SaaS and SaaS-enabled companies.  

‍

Why you need to care about net dollar retention.

‍

NDR provides a revenue-based view of customer retention. NDR is increasingly important as you scale from a small to a medium-sized business and beyond. For example, a $5MM business that churns 20% can replace that $1MM with a net new business when it’s growing by +50% a year. But when a $30MM business needs to replace $6MM this becomes insurmountable especially if the growth rate is slowing. Understanding net dollar retention from the start will allow you to stay the course if your NDR rate is in line with or above average. Similarly, a low NDR score means you may have bigger challenges within your business you need to address before further investing in scale.

As with most things in business, the effects of NDR compound with time. It’s either additive or punitive with every customer that you acquire. This means that small upticks in NDR can add up to very large differences in total revenue over multiple years. For example, assume a business had $10MM in revenue last year and consistently generates 20% of revenue from new customers. Improving the  NDR from 95% to 105% may sound meager, but over five years the business will gain another $5MM in revenue. 

One of the biggest challenges within a business is knowing those small actions that have life-sized effects. Monitoring and tracking your NDR rate is invaluable in helping you build a sustainable business over the long term.

‍

How to increase your Net Dollar Retention.

‍

Net dollar retention is an important metric to track. So the question is... how can you start identifying those opportunities to grow and deliverable value at scale?

First, hire a great team of CSMs who know your customer's needs and pain points inside and out.

Second, develop more premium services to sell to your customer base.

While on paper, this sounds straightforward and doable. But frankly, this takes a lot of time, resources, and buy-in from management to create enduring impact. 

Now consider this.

What if you had a “tool” that could analyze customer emails, tickets, and conversations for important signals that are typically related to predicting churn?

Maybe something that could listen for suggestions about features and products that might accelerate value capture and lift revenue.

What if you could start such initiatives without major upfront investments in data infrastructure or change the way your teams work?

We may be biased, but here at Sturdy, we created that exact tool. Connect with a member of our team to learn how tracking NDR and other critical metrics can help take your business to the next level. 

‍

Despite customer intelligence still being an emerging field, there are already many incredible CI platforms that can help you get the most out of your data. Utilizing customer intelligence data will not only help improve your overall business strategy, but it’s also a powerful way to improve customer satisfaction and customer experience. 

‍

Data on its own isn’t beneficial. What matters is understanding the customer journey of your users and analyzing data, customer feedback, and customer behavior to make better decisions.

‍

But as with most things in business, not all customer intelligence platforms are created equal. Depending on your goals, the size of your company, and your budget, each platform has its own strengths and weaknesses.

‍

Whether you’re already sold on the value of customer intelligence or looking for ways to take your business to the next level, this article will cover everything you need to know about choosing the right customer intelligence platform for your needs. 

‍

Choose a customer intelligence platform that works well with your tech stack.

‍

Businesses today, on average, use 37+ tools across their teams and departments. Every department has its “go-to” tools. Yet, keeping track of all that data collected by these tools can take time, and it only gets more challenging the more systems your business uses. With so many silos, it can be impossible to understand all your data in aggregate.

‍

When choosing a customer intelligence platform, the platform you select must integrate deeply with the critical components of your current GTM tech stack.

‍

For example, at Sturdy, many of our customers use Salesforce, so we began focusing on Salesforce integrations for our customers who rely on using the most popular CRM in the world. A customer intelligence platform can have flashy dashboards. Still, it will be challenging to realize game-changing value if it doesn’t pull the full payload from your CRM. 

‍

At a minimum, buyers must choose a system that integrates directly into your CRM, email, and ticketing system. Be skeptical of CI tools that claim to integrate with hundreds of tools “out of the box.” Chances are these systems are using a third-party integration platform. While third-party integration platforms are great for some things, they can be limited when ingesting data from custom fields. And otherwise, they represent another failure point on the reliability daisy chain. 

‍

Many CI platforms, such as our platform, Sturdy, become more valuable with more data they access. To that end, it’s essential to identify your largest customer feedback channels. For most of us, it’s likely email. Our research has shown that over 60% of B2B customer-to-business conversations are over email. This makes a tight integration with your email platform imperative. The right CI tools analyze email, and then and only then can they give you predictive customer intelligence data based on the bulk of your everyday customer interactions.

‍

Pro tip: When considering customer intelligence platforms, integrations matter. Choose a system that has authorized integrations with your other vendors’ marketplaces. Avoid systems that rely on third-party integration platforms. And, if email isn’t a core integration, you’ll likely be missing the lion’s share of insights about your customer relationships. 

‍

A secure, privacy-first customer intelligence platform

‍

Let’s face it, there’s a consummate conflict of interest in businesses today. Business units must leverage data to turn raw information into actionable insights. On the other hand, InfoSec and privacy teams must ensure compliance with a myriad of regulations relating to collecting and using data, mainly when it contains PII.  

‍

Personally identifiable information or PII is any information that permits an individual’s identity to be directly or indirectly inferred, including any information linked or linkable to that individual. But, if you collect someone’s name and email address, you are collecting PII. For this reason, you must choose a CI platform designed for the privacy-first era. Anything less is asking for trouble. Here are some tips to get started:

‍

First, ensure your potential partner maintains an information security program certified by yearly SOC2 Type II audits. This protects the security, availability, confidentiality, integrity, and privacy of their services and your customer data.

‍

Next, understand each provider’s approach to processing PII. Being SOC 2 Type II isn’t really about privacy. Otherwise, it’s essential to know if a vendor’s employees, consultants, or sub-processors have access to your customers’ PII. If they do, this is a problem. Look for a solution that offers a virtual data clean room. This way, you can ensure that data from different systems, including email, ticketing, and customer relationship management (CRM), is securely funneling into one spot. This data is encrypted and then anonymized, making it impossible for anyone in the data clean room to access PII. 

‍

Choose a customer intelligence tool that gets buy-in across all your teams. 

‍

There are very few teams in a SaaS business that don’t need more insights about customers. Customer intelligence is something your entire company should be involved in. Everyone in your organization will benefit from your chosen customer intelligence platform, from engineering to product to marketing. 

‍

When choosing a CI platform, consider the following:

‍

• Insights for various teams: Customer Intelligence isn’t just for customer success teams. Product and engineering teams can immediately benefit from learning more about customer frustration, confusion, and wants directly from the voice of the customer. Marketing teams can transform positive insights into customer references. Rev Ops and the BI team can create new analytical frameworks from previously unavailable data.   

‍

• Fast time to value: Let’s face it, we’ve all bought platforms that were oversold, hard to implement, and even harder to administer. Look for solutions that can deliver insights to your specific use cases quickly. Understand the resources required to start receiving value and what resources are needed to maintain the program in the future. 

‍

• Tech stack: When choosing a customer intelligence platform, the platform you select must integrate deeply with the critical components of your current GTM tech stack. And don’t forget email. 60% of customer-to-business communications start with an email. 

‍

• Avoid duplicate functionality: CI platforms often have similar functionality to systems you already have, like customer success platforms and CRM systems. Look to compliment your existing system with rich data from a customer intelligence solution. 

‍

• Security: Does the platform have a clear and transparent take on data security? Ensure that any system you choose is SOC 2 Type II ready.

‍

• Data privacy: How does the platform handle data privacy? Is the vendor using anonymization, pseudonymization, and de-identification techniques?

‍

Customer intelligence is not a magic bullet: Avoid platforms that make incredibly bold claims.

‍

It’s essential to have realistic expectations when choosing a CI tool. Just as AI-driven content marketing can be helpful for copywriting and content marketing, it won’t do all the legwork for you.

‍

This advice applies to customer intelligence platforms and any SaaS tool your business might use. Many “all in one” tools or “magic bullet” solutions claim they can do everything. But remember, the more the vendor tries to do, the more likely they, too, have “soft spots” where the technology isn’t good. 

‍

At the end of the day, a customer intelligence solution should help you operationalize your practices and programs and get your entire organization enthusiastic about using insights to improve products, drive growth and expansion, and, ultimately, increase your NDR. Find solutions that demonstrate a clear path to value in the shortest time. These are the solutions that the C-suite can fund. 

‍

Finally, customer intelligence is a hot topic. But it’s not exactly new. So with the tremendous growth in the CI world, some organizations have failed with products that don’t deliver value. The good news is that integrations, data sciences, and privacy tooling have all dramatically improved in the past 3-5 years. This has made products more powerful and easier to maintain.

‍

Turn customer feedback into actionable insights. Get clear on your CI goals.

‍

Customer intelligence tools continue to innovate incredibly quickly, but choosing a tool that serves your specific needs will make or break your experience. 

‍

Perhaps you’re really focused on reducing churn. You may want a platform that streamlines your data points in one easy-to-read channel. Improving your customer experience is your number one goal. Increasing customer lifetime value, for example, is a common goal regarding competitive intelligence.

‍

Of course, you’re almost certainly going to have multiple business goals. Still, it’s critical to have a clear idea of what you’re hoping the CI platform can help you accomplish from the start. Before you schedule a demo or request more information, have 2-3 specific goals in mind. 

‍

Invest in both the now and the future with customer intelligence

‍

There are significant gaps between what customers think about your products, the level of services you provide, and the execution of the journey you’ve outlined. The question is, “how seriously are you taking their feedback”? How closely are you listening to your customers? Churn doesn’t happen in a vacuum. It’s a culmination of feature requests, “how to” questions, executive changes, response lags, unhappy sentiment, and more. The right customer intelligence must deliver the insights to help teams create more enduring relationships with arguably the most significant cohort of humans outside your employees — your customers. 

‍

While customer intelligence 2.0 is still in its infancy, businesses that utilize modern CI solutions effectively have a clear competitive advantage over those that do not. Nothing speaks louder than the voice of your customer. Today’s customer-obsessed teams make better decisions based on insights into the data customers generate for us with every conversation.

‍

Interested in seeing around the corners? Learn where customer intelligence is going. Schedule a demo with Sturdy today.