SaaS customers won’t be successful with a SaaS product if they don’t use it. Sure, some might continue to pay for it (seriously, my dad’s still paying for AOL), but that’s not the same as success. And you want people to be successful with your SaaS product (retention revenue, anyone?)
Enter your customer success team — their job is to maximize engagement with the product. Account not engaging? Fix it. Account engaging? Excellent, increase engagement even more.
But CS teams can’t work blindly (or they shouldn’t if you want them to be successful). So how do you remove the blindfold? It’s elementary, my friend: Product engagement — the system upon which all other customer success metrics are built. Metrics based on product engagement give your team a glimpse into the health of the business. And they’re actionable (CS teams need to take action).
Here are the key customer success metrics you should be tracking:
Product Adoption Rate
Activation Rate (for new accounts)
The “What” of Customer Success Metrics
Customer Success Metric #1: Active Users and Accounts
active user (n.) = someone who has used the product in a given time frame (even if only a little!)
active account (n.) = an account that has had at least one user use the product in a given time frame (even if only a little!)
Then choose how often to measure (this will depend on your product). Used daily (think Facebook)? Measure DAUs. Used monthly? Measure MAUs. Most SaaS products are business apps with weekly usage patterns so a WAU customer success metric works best.
Here’s a pro tip: SaaS businesses are account-based businesses and your customer success team operates at an account-level. If you can’t measure your key product engagement metrics at the account level, then they’re not helpful. Action item: Make sure you can determine“active” for users as well as for accounts.
Generally speaking, “active” is a pretty shallow metric. To get a better understanding of how well your customers are engaging, you need to look deeper.
product engagement (n.) = a measure of how engaged your users or accounts are in a given time frame
This is this singular customer success metric for any SaaS business. You already know “active” doesn’t mean “engaged” (neither does “last login”). Product engagement is more than that. Just ask Lincoln Murphy:
Logins Don’t Matter
While you generally need to sign-in to an app to get value, that action alone is probably not the thing that delivers value to your customer.
Simply being “active” in the product doesn’t mean you’re being “successful” either.
In fact, a lot of logins and random in-app activity could be a sign that your customer can’t figure out what to do…but they sure would like to.
Crazy, indeed. You need to score actual product engagement. It’s a model that scores each of your users based on (a) the number of times they do certain things in your product; and (b) the importance of those activities.
Here’s what a table to score user engagement might look like:
Importance (between 1-10)
Number of Times Triggered
Total Raw Score
By doing this you will give every user his/her own engagement score (you should then normalize the scores between 1-100 so they are easier to understand and use) for your engagement period (daily, weekly, monthly — up to you).
Any system you build (or use) for measuring engagement should help you measure engagement at the user, account, and product level. And it should track this engagement over time. If you want to get value out of it, anyway. You do want to get value, don’t you?
Customer Success Metric #3: Product Adoption Rate
user adoption rate (n.) = the percentage of your key features a user has used in a given timeframe
account adoption rate (n.) = the percentage of your key features any user from an account has used in a given timeframe
Measuring Adoption is similar to measuring engagement, but Adoption determines “what percentage of your key features” your customers are using. While users can show strong engagement by only using a small set of features, Adoption rate measures the number of unique features being used. This basically measures “depth of engagement.”
For example, if you have ten important features and one of your accounts has used two of them in the past month, that account would have a 30-day Adoption rate of 20%. But another account whose users used eight of those features would have a 30-day Adoption rate of 80%.
Low Adoption rates mean that users are using the product in a concentrated way, while high Adoption rates mean that users are using the product more broadly.
Customer Success Metric #4: Activation Rate
activation rate (n.) = How far along a user/account is on the path of becoming Activated, i.e. fully on-boarded and/or to first-value
Knowing how close (or far away) your accounts are to the point of Activation is an essential customer success metric for any team working to onboard new users.
An Activation rate is just that. It’s a measure of what percentage of your “Activation” criteria an account has met — how many steps have they taken as a percentage of the total number of steps they need to take. (This is especially important in trial accounts.)
For example, if you offer a project management application, new (trial) accounts might be Activated after they:
Create an account
Invite 2+ team members
Create a project
Upload 2+ files
Create 3+ calendar events
Create 1+ tasks
Complete 1+ tasks
For this product, accounts that do all of these things would be considered Activated during their trial. The Activation rate would be expressed as a percentage based on how many of these steps a new account has taken.
The “How” of Customer Success Metrics (How to Use Them, That Is)
You’ve got the what, now let’s figure out the how to (assess and derive action from) of our core customer success metrics. To do that, we need to get them actionable at both a management and a tactical level (as with any other operational metric).
Management-level metrics tell you about the health of some part of your business. A management-level customer success metric tells you about the health of your paid user base (or specific segments of it).
Tactical-level metrics are action metrics. They tell your team that something needs to happen (or not happen). A tactical-level customer success metric is all about helping your customer success managers identify issues and opportunities so they can take action. Baker Street Insight: These metrics really need to be measured at both an account and user level.
Excellent! Let’s see how to use the key customer success metrics we defined above.
Customer Success Metric #1: Active Users and Accounts
This one’s inherently more tactical. And why? It doesn’t do much to tell you about the health of your business other than painting a picture of (a) the general scope of your user base and (b) it’s growth (or decline).
Knowing if you have 200 active accounts (or if the number of active accounts is different from last month) can help you plan resources at a management level. And if you don’t have a product engagement scoring solution, you could use growth in active users/accounts as a proxy for the health of your product. But you really shouldn’t (see above).
For tactics, on the other hand, knowing how many active users there are on a specific account is very helpful for a CSM managing an account. Most SaaS businesses can only be successful for their customers if the product is used by multiple users on multiple teams. So when managing SaaS accounts, knowing the number (or percentage of active users) can help a CSM identify problem or thriving accounts and prioritize their work.
As a management metric, tracking the engagement level of paid accounts over time tells you the overall health of your userbase. Are our paid users becoming more or less engaged with our product? This is a basic question that all Customer Success teams should be able to answer.
It also is a customer success metric perfect for assessing the health of different segments of your customer base. For example, looking at the engagement of accounts at different pricing plans or in different industries can help you hone your ideal customer profile (product-market fit, anyone?). Interesting use case: Looking at the engagement of accounts by individual CSM is one way to assess CSM performance.
As a tactical customer success metric, looking at product engagement score at the account level can uncover:
Highly engaged accounts that can serve as your best advocates
Accounts that are at risk of churning
Accounts with engagement growth that may be ripe for potential expansion
Accounts that may have had some turnover and need attention
At the user level, this metric can help you identify power and problem users. Power users (or power users for each account), my friend, are going to be key to the health and potential expansion of an account. Problem users (those whose engagement is decreasing over time) can quickly become the canary in the coal mine for any account. Use them to gain information.
Customer Success Metric #3: Product Adoption Rate
Let’s get real here: One of the main jobs of your customer success team (and one of the hardest) is getting users to adopt as many of features as possible. Healthy businesses have healthy Adoption Rates and looking at an overall Adoption rate for your paid users can help determine whether or not this is happening.
As with Engagement Score, looking at Adoption rates across different segments can also be helpful. You may have accounts that are on self-serve plans vs high-touch service plans — looking at Adoption rates across these two segments can help identify if your high-touch efforts are helping. (The same is true for looking at Adoption across different pricing tiers.) Looking at Adoption rates across various segments can offer insights that can help drive higher-level customer success strategies.
As a tactical customer success metric, it’s important for you customer success teams to know the Adoption rate of their accounts so they can effectively target accounts with specific and relevant support. An Adoption rate metric at the account level can help a CSM understand each account’s use case and and give them the information they need for futher Adoption.
Customer Success Metric #4: Activation Rate
Activation rate is a customer success metric targeted at your new accounts and users — and it’s an important one. Looking at Activation rates at a management level can help you understand the success of your on-boarding efforts.
But when you track Activation rate at the account level, it becomes a powerful tactical customer success metric. Every customer success team is responsible for on-boarding users and accounts, so having the ability to track the degree to which each account is on-boarded is essential for prioritizing and organizing their work. Having this data can help a CSM focus on those accounts that are stuck in the process and understand exactly what the sticking points are.
Product Engagement Metrics Are Foundational for any SaaS Customer Success Team
Quite so! Operational metrics give you insights into the health of your business, but when used correctly, they are also powerful tools that help you define specific actions. The former management-level use case dovetails nicely with the latter tactical-level use case.
This is especially true when it comes to metrics for your Customer Success team. Without customer success metrics that can inform and drive action, your team will be spending a lot of time guessing and chasing after red herrings. Not excellent.
In today’s game of SaaS (you know it’s a game, right?), success depends on knowing what’s going on in your business. And acting on that information — fast. Not sure how? Enter Sherlock’s product engagement Alerts.
Now customer facing teams at any SaaS business can stay on top of how users are engaging (or not engaging) with the product in real time.
Product engagement alerts? Curious, but of what would I need to be alerted?
A remarkable question, indeed. There’s a lot of engagement alerts your team might welcome — some unique to your SaaS business, some not. Here are few game-winning no-brainers to get you started:
SaaS Product Engagement Alert #1: New account sign-up
There is no greater rush (except perhaps the one felt by Sherlock when a fresh stream of liquified opium kissed his bloodstream after an extended stretch of abstinence) than seeing a new account signup for your product. They love us! What better affirmation of your collective efforts?
This one is for sharing. Set it up. Celebrate. Pop the champagne. But, wait, don’t forget about the account! Make sure you’re moving them toward a more significant commitment.
By the way, once you’re getting too many signups for a realtime alert (it’ll happen!), you may want to set up a daily summary for all the good news.
SaaS Product Engagement Alert #2: Account converts to paid
Well done, my friend! You converted that trial too paid. Push this product engagement alert to a group channel and let the GIF party begin.
SaaS Product Engagement Alert #3: New users added to existing accounts
Don’t let these ones fall through the cracks. New users added to your existing accounts might not have been critical to the account converting to paid, but they’re going to be critical for retention. These are the people using your product. If they’re not onboarded correctly, you can kiss your retention revenue goodbye.
Instead of ignoring these users, set up an alert for your CS team so that they can not only become aware of these new users, but can reach out and give them a great initial experience with your product.
**Bonus! Set up this alert for your trial accounts as well Adding new users to a trial is a strong signal of activation and potential conversion.
SaaS Product Engagement Alert #4: Trial accounts become activated
Got some people on free trials? You need to know when these accounts become activated. Well, if you want to hit your sales number. When a trial account becomes activated, someone should be reaching out — or at least strategizing the next step in the sales process.
Don’t miss the opportunity. Set up an alert for when an account becomes fully (or partially) activated.
This one’s not great, but it’s not a prescription for doom either. A drop in the engagement score of any account is an important signal of potential trouble. Set up an alert for whenever a key account’s engagement drops more than, say, 20 points so that your customer success team can do something about it. There’s still time to stop the churn.
SaaS Alert #6: Account becomes inactive
A drop in engagement score is one thing — you can recover from that. Complete inactivity is another (it’s definitely worse). A completely inactive account is a churn threat of the highest order — a true emergency. This alert may give you one last chance to save an account.
SaaS Alert #7: When an account’s engagement score increases significantly
Time to celebrate again. A rise in an account’s engagement score is a great signal for the health of the account — and, you guessed it, a great signal they’re ready to expand. Set up this alert and get your customer success team on top of your best accounts so they can start expanding.
You spent months on that new feature — users have to love it, right? See how and where it’s being adopted in real time by setting up this product engagement alert. The product people in your #product channel will be thrilled and, more importantly, they’ll know which features are being used and which aren’t. That’s more information for the next one!
SaaS Product Engagement Alert #9: When account triggers at-risk features
Many products have features that indicate someone’s going to drop out. We’re looking at you data exports, paused messages and deleted projects. You know you have the actions. You know you don’t want people to use them. Don’t you wish you knew when people were? Create an alert for the use of these features and give your team the chance to save at-risk accounts.
SaaS Product Engagement Alert #10: Cancellations
Ok, it happens, not all accounts can be won. We know it’s tempting to pretend it doesn’t, but this is a great opportunity to learn what you can do better. The moments after an account cancels are prime time opportunities for feedback. The battle might be lost, but don’t lose your chance to collect the game-winning move.
The SaaS business model has long challenged the need for the traditional software salesperson. The SaaS model – and more recently the push toward Product-Led Growth with its free trial and frictionless upgrade path – has called for the death of sales.
The SaaS business model has long challenged the need for the traditional software salesperson. The SaaS model — and more recently the push toward Product-Led Growth with its free trial and frictionless upgrade path — has called for the death of sales.
“Why do we need a sales team if a customer can try, use, and buy my product without talking to anyone?!?!?”
Of course, this has proven to be a bit hyperbolic. A high-performing sales team is still an essential part of most SaaS businesses.
With that said, this new software model has certainly redefined the way that a software sales team operates in fundamental ways.
Most significantly, the product-first model means that it is very likely that your salespeople are selling to people who have already started using your product. These prospects are either on a free trial, using a freemium version of the product, or maybe even in a pilot. No longer are your sales people selling an abstract concept to some bureaucratic decision makers. They are selling to actual users. People who have experienced the product in some way. Hopefully seen some value – or not.
This means that for any sales team to be successful in this new world of software, they need to pay attention to things they haven’t had to in the past — most significantly product engagement.
Product engagement in the SaaS sales process
Selling to someone who has used your product is different than selling to someone who has not. In order to sell to people that have used your product, it is essential to be intimately in touch with:
how they have used the product;
how far they have gotten toward Activation;
what feature they may have missed; etc.
If you are selling a product with a freemium or free trial experience, this information, this data, is a new requirement in the sales process. In fact, this data is the basis for a Product Qualified Leads (PQL).
Want to learn how Sherlock can help your sales team get what they need? Click here.
Given that factoring product engagement data into a sales process is still a new concept, we wanted to outline the five things that your sales team will need with regards to product engagement data. Whether you are building your own internal systems for this or using a solution like Sherlock, this is what you team needs:
Access to the data
Obviously, getting the end users – in this case your sales team — access to the essential data is a fundamental part of any data-based process. But access is one thing — easy access is another thing. You need to understand the most convenient places for your sales team to consume this data. Obviously, that’s your CRM (Salesforce?) – where your sales team spends the most of their time. But don’t overlook some other places where they may like to see this data — namely Slack (and potentially Intercom). Don’t think you can throw this data into a spreadsheet and think your team will use it. They won’t.
The data in a usable format
Having access to the data is certainly necessary. But your product generates a lot of data. You can’t dump a truckload of raw engagement data from your product onto your sales team and expect them to makes sense of it. This data need to be compiled into a format that has context and is easily consumable. You should create a methodology to score and rank your users based on how frequently they are using the most important parts of your product (learn how to do that here). Doing this will allow you deliver this data to your sales team in a format they can actually use. A simple way for them to understand who’s engaged, at what level, and how recently. Again – the more voluminous and complicated the data you give your sales team, the less likely they will use it.
Engagement scoring at the account level
This is super obvious – so much so that it’s very easily overlooked. As a SaaS business, you don’t sell software to individual users. You sell to teams, to organizations — to accounts. This means only tracking product engagement at the user level is not helpful. You need to be able to aggregate this engagement data at the account level. Without this ability, your PQL process will become more frustrating than helpful and your sales team will likely abandon it.
Ability to identify the most engaged users on each account
When working a sale, salespeople are always looking for the right “entry points” into an account. They look for people who are going to become their internal champions — someone who will help sell the product internally. Therefore, having insights into the engagement of each user on an account is essential for driving a sales process. The users most engaged with the product will become “case studies” your AEs can use when trying to sell to other decision makers. This is key, key data for your sales team.
Ability to track account Activation rates
The goal of any trial process is to drive users and accounts toward “Activation.” Every product has a different definition of Activation, but it’s generally the three, four, or five specific actions that allow a new account to experience “first value.” A good PQL process will include insights into the Activation progress for every trial account. Which accounts are fully Activated? Which ones are almost there? Which ones are way off? These are all essential questions your sales team are asking and which that should be easily answered in your PQL process.
Whether they like it or not, modern sales people at modern SaaS organizations must become very familiar (and very comfortable) with product engagement data. In fact, this data is quickly becoming the most important qualification criteria for potential customers – the basis for the Product Qualified Lead. When you are selling to people who have used the product, knowing how they are using the product is simply, essential.
But it is not easy to get this data compiled in a way that it can be effective for your sales team. We hope this list of requirements provides a good start for putting together this type of system.
If you’d like to see how Sherlock can make this a reality with very little effort on your part, click here.
One of the most common (and existential) questions I get when it comes to product engagement in a SaaS business is: “Who owns customer engagement?”
What the asker means by this is: “What department owns customer engagement?” Is it product? Is it customer success? Is it product marketing? Is it growth?
These are questions around which passionate discussions are had, but they don’t do your business any good. They all stem from a common management practice demanding that all major metrics be owned by a specific person or department:
Marketing owns leads
Sales owns revenue
Customer Success owns churn
Finance owns profitability
Why does one department need to own a metric? (Hint: It’s rhetorical, they don’t) Especially in collaborative environments (just ask filmmaker Stephen Daldry).
Like film, customer engagement is a collaborative exercise. Do you know what makes collaborative endeavors successful? When EVERYONE owns a piece of EVERYTHING.
In the production of a film, there are many people, and many departments, whose work must come together in order to build something great. To try to manage this complex organism by creating artificial ‘ownership walls’ would be a disaster.
Ownership of high-level, output metrics in a SaaS business is the same. We’re looking at you, customer engagement.
The better question: What contributes to customer engagement?
Stop asking “Who owns customer engagement?” Seriously, stop it.
Go beyond the who and look at the what and you can start to unravel the truth of this matter. So, what does contribute to customer engagement:
The concept: Let’s start right at the beginning. If you are building a business on top of a concept that just doesn’t provide much value — or one that doesn’t solve a problem — it will be awful tough to drive sustainable engagement.
Initial expectations: Mismatched expectations can be a killer for customer engagement. If users expect something different than what your product delivers, it’s going to be very hard to keep them engaged (even if your product does provide some value).
Theproduct: Obviously, if you build a crap product – your engagement will follow. Even if you are solving a clear pain, if the product doesn’t deliver with key, valuable features then users — well — they won’t use it.
Usability: Not only does the product need to deliver on key features, but it needs to do so in a way that allows users to easily derive consistent value. And the more delightful the experience, the better. If the product is simply too hard to use, you aren’t going to see good customer engagement numbers.
Onboarding: More and more, good onboarding is becoming essential for laying a good foundation for engagement. If you can’t quickly and efficiently get users to the value of your product, you’re going to have a hard time keeping them engaged for longer than a week or two.
Integrations: The more your app is integrated into the normal workflow and experience of your users, the more engaged they will be. And this includes both technical and non-technical integration. The technical integration makes sense. If you have an email support app and it integrates with Gmail, you’re going to see higher customer engagement from Gmail users than if you don’t. If you have a sales-related app and don’t integrate with Salesforce — good luck. Offline, if your product works very naturally into the regular flow of someone’s work/activity/behaviors, you will see stronger customer engagement.
Education: Keeping users educated with ways to continuously drive value from your product is essential to driving customer engagement. This can take on the form of in-app help/support assets, marketing messages, training webinars, certification programs, user conferences, etc. Education is a big deal for driving long-term customer engagement.
Social connection: This is not something that fits in many engagement checklists, but don’t ignore it. Products that build communities around themselves, ones that offer ways to socially connect with other users, can reach major heights in customer engagement.
Trust: Yes, more of the soft stuff. But again, don’t underestimate its importance to customer engagement. In this case, let’s look at the opposite of trust — that’s lack of trust. If users don’t trust your app (e.g. they don’t think their data is secure; or they don’t trust the output of your reports; or the product is generally unreliable) or your team (e.g. support requests go unanswered for days; the CEO is caught lying in the press; management is under indictment), you are going to lose customer engagement.
Pricing: Hear me out. Pricing does play a (small) role in customer engagement. There are some pricing models that actually dissuade more usage, so it’s definitely something to keep in mind.
Continuous awareness: This is super important in today’s world. With short attention spans and a zillion apps competing for that attention, simply keeping users aware — let alone engaged — with your product is a huge challenge. Be sure, without awareness, there is no engagement.
Those are just a few of the things that go into overall customer engagement. But the point is this — there are MANY things that contribute to customer engagement.
So how does this map back to the original question – Who owns customer engagement?
It’s quite clear to see by looking at the above list that the things that contribute to strong customer engagement do not live in a silo and therefore cannot be managed in a silo. If you were to translate the list of things that contribute to customer engagement into the departments that impact these things, you would have a diagram that looks something like this:
It’s impossible to assign responsibility for customer engagement to one specific group. Everyone in the organization is responsible for it.
The best question: How can we actually drive better customer engagement?
Not ready to let go of the ideas of ownership and accountability? That’s ok.
For the rest of us, this next part should be easy. It’s now time to make the shift from the original question of who owns customer engagement to the more important question: How can we drive better customer engagement?
We should be focusing, not on who, specifically, is responsible for customer engagement, but how we can be improving it.
This question leads to the right conversations. It leads to actionable strategies and takeaways. It helps bring the team together around a common goal and attack a part of your business that demands an “all-hands-on-deck” approach.
As you transition away from the question of who to the question of how,there are a few basic tips that can help you be more successful in your efforts.
Measure it. First and foremost, you simply can’t manage customer engagement if you aren’t continuously measuring it. This is an important starting point. Whether you use Sherlock for this or not, it’s essential that you find some way to quantify your customer engagement before you can think about improving it.
Treat it as a KPI. Again, customer engagement is the lifeblood of your entire SaaS business, so you need to treat it with the appropriate level of priority. Customer engagement should be a KPI of which everyone in the company is acutely aware. It’s a metric that should be discussed at every exec and board meeting and treated like a true indicator of the current and future health of the business.
Make sure everyone is aware of their part. Make sure that everyone on the team is aware that this is a metric that no one group owns. Have that discussion as soon as possible. More importantly, as part of this discussion, help everyone understand the part they play in driving customer engagement. Come to an agreement on clear and specific initiatives that each group can contribute to driving great customer engagement.
Treat it as a life-long pursuit. Customer engagement is not something you solve once and move on. For as long as you have a product — for as long as you have a SaaS business with customers — you are going to be fighting this battle. Treat customer engagement with a long-term mindset and manage this metric like your business is riding on it (because it is).
It’s our customer engagement
If you have a highly engaged user-base getting value from your product, most of the time, things will work out well for you. Sure, you need good sales, good marketing, strong cash flow, etc. But generally, all of this will fall into line if you have great customer engagement.
But you can’t achieve high levels of customer engagement by unnaturally forcing it into some management silo. It’s an element of your business that requires a unified, holistic approach. All hands on deck.
As Stephen Daldry might say: it’s OUR customer engagement.
If you’re reading this, it’s safe to say that you’re already doing a pretty solid job of tracking your product data. You’re probably generating piles of data on your users’ activities every day—how users are interacting with your product, what features they’re using, how frequently they’re being used, and so on. But just how much mileage are you really getting out of this data?
When it comes to tracking product data, chances are that you are using some type of general analytics tool (which is nothing more than a dumb query interface), which allows you to pull up and visualize your product data in various ways. Perhaps you’re taking this one step further, making this data available to other teams in order to help them make decisions and drive specific actions. You might even be using Segment.com to facilitate this distribution (which I couldn’t recommend more).
However, very few people are taking things to the next level by infusing their raw data with context , giving it meaning, and making their product data not only accessible, but actually useful to other teams within their organization.
Raw data is good. However, for many people, it’s just not that helpful, and it’s definitely not scalable. Sure, for those brilliant data analysts, raw data is awesome. In fact, data analysts prefer the data to be as raw as possible!
However, when you are trying to leverage data in order to drive decisions and actions, it needs to be easier to consume. This is especially true when you are trying to scale the decisions and actions that can be derived from this data across a wide group of people.
Let’s take credit data as an easy example. The average adult’s credit history includes mounds of raw data, all of it super valuable. But without any context, how useful is it?
Raw credit data looks a little something like this:
January 2010: Opened credit card
May 2010: Car loan issued — principal $13,500
June 2011: Late payment on car loan
July 2012: Applied for mortgage
August 2012: Late payment on car loan
Feb 2013: Opened credit card
Feb 2014: Credit card limit extended
May 2014: Car loan balance paid in full
May 2014: Mortgage issued — principal $159,400
July 2014: Credit card balance paid in full
Dec 2015: 90-day delinquency on mortgage payment
Based on this raw credit data alone, would you be able to tell if this individual’s credit history is good or bad? If you were a bank, would you lend to this person? How would you make that decision?
If a creditor had to weed through all of this raw data every time they were assessing a loan, well, there wouldn’t be many loans issued. Not only would take an enormous amount of time to weed through this type of data, but it would also be near impossible to leverage for decision-making purposes.
By just looking at this data on its own, some might think, “Three late payments over 5 years? That’s terrible! Reject him the bum!”
But what if told you that the average potential borrower had six late payments over a typical five year period? Hm….maybe this individual’s credit history isn’t looking so bad.
However, what if I then told you that 8% of the population had zero late payments over five years? Oh…interesting. So this guy’s not terrible, but not perfect, either.
Now, what if I told you that this borrower was in the bottom 25% of credit holders in terms of length of credit history? Well…jeez.
The point is, this raw data is really meaningless without the right context. No lender could ever be expected to make a good, fast decision based upon raw data alone.
Enter credit scores.
Credit scoring models take in all of this raw data and spit out a contextual number that is actually useful. They weigh certain factors (like payment history) more than other factors (like total amount owned), crunch the numbers, and churn out a single number. And with a scoring model, it all becomes pretty simple to determine that someone with a 750 credit score is a better borrower than someone with a 670 credit score.
The best part is, it’s scalable. Any type of creditor — mortgage lenders, car companies, rental agencies, etc. — can use this same number to drive their decisions.
In short, it’s helpful, actionable, and scalable. Because it has context.
Adding context to your product data
One of the best ways to add valuable context to your existing product metrics is by creating a way to score your product engagement. Like with credit scoring, product engagement scoring gives your product data the essential context necessary for every part of your organization that relies on it.
Ultimately, this contextual product data is essential for:
Helping Sales assess trial leads. If you have a free trial or freemium model, tracking activation metrics will help sales prioritize their efforts.
Allowing Marketing to build more relevant and effective messaging. For most SaaS business, much of your messaging should be shaped and triggered based on engagement (or lack thereof).
Prioritizing customer success efforts. Targeting upsells, saving failing accounts, providing highly relevant support—all of this can (and should) be driven by account-based engagement metrics.
Helping the board make future investment decisions. Strong user engagement is indicative of future success. Poor engagement is, well, not.
With context, this type of data can—and should—become a foundation for much of how you conduct your business.
How Sherlock handles engagement scoring
While Segment.com has provided a tremendous service for making product metrics available, Sherlock was designed to make this data useful.
In Sherlock, users create their own scoring model by weighing their important product events based on each event’s importance to overall engagement, much like a credit score. With this simple configuration, Sherlock builds a model that gives every user of the product a normalized score between 1–100.
As you can imagine, these normalized scores make your product engagement data helpful. They allow you to understand engagement like never before. Sherlock leverages these user-level scores to score and rank:
All of your active users
Each of your accounts
All product features (based on engagement)
Segments of users
The engagement of your product over time
All of this data can be easily consumed because it’s all contextual. More importantly, this scoring model enables product data to be much more useful and actionable across your entire organization.
Start taking your product data to the next level
Don’t settle for weeding through a bunch of raw data to derive meaning. And certainly, don’t make the rest of your organization wrestle with your raw data in order to make their functional decisions.
Whether or not you use Sherlock to help with this, you should definitely be looking to give your product data more context. To help you get started on your own, we’ve created a step-by-step blog post on how to track product engagement.
The fact is, SaaS organizations that make decisions and take actions based on actual user data simply operate at a higher level. As a product leader, you should be striving to make this as easy as possible for the team. Facilitate the transformation of your product metrics and get the entire organization to the next level.
If you’d like to see how Sherlock can help add valuable context to your existing product metrics, you can start a free trial or request a demo.
“There is nothing more deceptive than an obvious fact.”
― Sherlock Holmes, The Boscombe Valley Mystery
The Power of Account-Based Product Engagement Insights
By and large, SaaS businesses are account-based businesses. Most SaaS companies don’t build or sell products that are intended to be used by a single user—they build and sell products that are intended to be used by a collection of users, teams…people across an entire organization.
In short, SaaS products are built for accounts.
This is why it’s essential to able to assess our SaaS businesses through this lens—the lens of “accounts”. Marketers have acknowledged this fact and have made account-based marketing (or ABM) the hottest trend in marketing over the past few years.
The same goes for product engagement. The ability to understand, assess, and act upon product engagement metrics at an account level is essential for any SaaS business.
By not viewing product engagement through an account lens, you could be creating a significant blind spot across your SaaS organization, limiting the effectiveness of your entire operation.
That may seem hyperbolic, but it’s really not. Tracking and assessing account-based engagement (or ABE) for your product can help your SaaS business work smarter and become more effective.
By tracking and assessing product engagement at the account level, you will be able to:
Better understand and track account activation
Whether you have a low-touch, self-serve offering or high-touch, white-glove onboarding team, the ability to assess the activation progress for your accounts is essential.
To do this effectively, you must assess engagement at the account level. For most products, becoming activated isn’t something a single user can (or will) do. No single user will move through an entire onboarding process on his or her own. Most times, it will take multiple users to do all the things necessary to be considered “activated”. For example, for Sherlock, we generally see that it takes two or three users on a new account to do all the things that deem that account “activated”.
On a tactical level, the ability to understand the activation process will make your CS team much more efficient. By having clear insight into the onboarding progress of their new accounts, they will be able to easily prioritize their work on a daily basis. Some accounts will need high levels of attention, while others can be left to progress on their own.
On a strategic level, the ability to track activation metrics is essential for optimizing this initial part of your customer journey. In order to assess the effectiveness of your efforts at this stage, you’ll want to track things like:
Account activation rate (% of new accounts that become activated)
Time-to-activation (how long it takes accounts to reach activation)
Activation by account type
These are key metrics for any SaaS business, but they’re virtually impossible to find if you aren’t tracking account-based engagement.
Accurately assess the health of your mature accounts
For most SaaS businesses, the most significant account work actually comes after the onboarding period—team training sessions, feature adoption, ongoing value creation, account expansion, and so on. This phase is where the real value of a SaaS customer comes, and it’s all based on how your accounts are (or aren’t) engaging with your product.
As with the activation phase, the health of any given account will be less about how each individual user is engaging, and more about how the group of users that make up each account are engaging. Tactically, this is essential information to drive your post-sales operation. With this level of insight into account-based engagement, your team will be empowered to:
Determine which accounts are prime for expansion. Accounts with high engagement—especially those whose engagement is trending up quickly—represent great opportunities for expansion.
Identify at-risk accounts. Accounts with low or falling engagement represent a definite risk.
Improve feature adoption at the account level. Not all features need to (or even should be) used by every user on an account. However, as a whole, every account should use almost every feature. Having this knowledge will help drive your feature adoption efforts.
Ensure that important account segments are receiving the right attention. Looking at the engagement of accounts based on their tenure or MRR, for example, are great ways to prioritize CS work on a regular basis.
Any kind of health assessment in a SaaS business simply must be done at the account level. Not to put too fine of a point on it, but if you aren’t assessing account-based engagement for your product, you are essentially working in the dark.
Refine your acquisition efforts
The assessment of account based engagement isn’t just helpful for retention efforts—it can even help refine and optimize your top-of-funnel acquisition efforts.
“What? Huh? That’s ridiculous. Engagement is only about churn prevention.”
― Random SaaS CEO from 2012
Au contraire, my historic friend.
Let me ask you this: what if I gave your head of marketing a list of your most engaged and longest-tenured accounts. What would she do with that list?
If she’s a mediocre SaaS marketer, she would have a quick look, mutter something along the lines of “That’s nice to know,” and continue on with her day.
On the other hand, if she’s a smart SaaS marketer, she will drop everything, jump on a conference table and shout, “We’ve found it! The key to our future!”
A smart, modern marketer will understand that having a definitive list of your best existing customers can help her acquisition efforts by:
Improving her account-based marketing efforts. A smart marketer would use this list to identify the types of accounts that are most likely to be successful with her product. She would look at things like company size, industry, sector, use case, revenue, etc., and base her TAM analysis on that. She would then direct her budget to these opportunities.
Identifying great case study candidates. If these are the most successful accounts, then they will have the best stories to tell. These accounts will serve as the most positive and targeted source of social proof she could find. She would use these accounts as the basis of case studies, quotes, ads, advocate programs, and so on.
Driving look-alike programs. In today’s world, the technologies that enable a marketer to target “customers that look like these customers” is ever-expanding. For these programs, a list of the top, most successful accounts (and their users, in this case) is worth its weight in gold.
And this is just the tip of the iceberg for how a smart SaaS marketer could use this type of account-based engagement data.
But again, if you aren’t assessing account-based engagement, this is all just a pipe dream.
Optimize your sales process and finally start that PQL initiative
Do you have a freemium offering or a free trial for your SaaS product?
If yes, then I’m betting that you’ve also been dying to help your sales team (or if you operate like we do, your CS team) prioritize where to direct their energies on a daily basis.
In fact, you probably made a New Years Resolution to put together some kind of PQL (Product Qualified Lead) process for your team some time ago.
The fact is, any PQL program is completely based on product engagement at the account level.
Free trial account signs up → Accountcompletes some key events, scores high engagement → Becomes Product Qualified Lead → Salesperson goes to work
This process will make your sales team much more efficient, empowering them to focus and spend their time on the right accounts.
It’s a no-brainer.
But, it’s not possible without assessing account-based product engagement.
The SaaS world is an account-based world
These are just a few opportunities that will present themselves when you start assessing account-based engagement. While user-level engagement is important, SaaS businesses operate at an account level. You can’t do that if you aren’t tracking and assessing ABE for your product.
As a savvy SaaS operator, this focus on account-based engagement may all seem incredibly obvious to you. However, the reality is that most SaaS businesses are not looking at product engagement this way.
The reality is that it’s not that easy. And up until now, there weren’t any products that took ABE on as a primary goal. Call it evolution. The SaaS model has matured, product engagement assessment has matured — it seems only natural that assessing product engagement in a way that more closely matches the operating model of a SaaS business would come along.
When we built Sherlock, this was one of our main goals. We wanted to close this gap and give SaaS businesses an easy and effective way to operate around account-based product engagement.
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