User Analytics & Segmentation
  • In order to do engagement well, you need to first understand how users use your product
  • You should be able to measure the impact of walkthroughs and onboarding engagements on adoption and retention – the metrics you actually care about
Application Performance
  • In-app walkthrough guides and engagements shouldn’t come at the cost of application performance
In-App Engagement and Walkthroughs
  • Guides shouldn’t be static; it should be possible to target, personalize, and throttle engagements based on account / user characteristics
  • Enable realtime throttling of engagements based on user behavior or areas of product friction
Cross Channel Engagement & Collaboration with Customer Success
  • Your Success team is working hard to drive adoption and deepen relationships with customers; your strategy — and systems — should be aligned.

User Analytics & Segmentation

The first step in any user engagement strategy is to deeply understand how your users are behaving within your product. These are questions like:

  • Path analysis: Where are the “choke points” and usability challenges in the adoption journey?
  • Adoption analysis: Which features perform well? Which engagements are effective at driving usage?
  • Retention analysis: How sticky are specific product features and what is our window of opportunity to engage before users fall off?
  • Funnel: Where exactly are users dropping off and how can we optimize the adoption path?
  • Cohort analysis (queries): Compare user and behavioral cohorts to learn about growth

With this type of pre-built and custom analytics, you as a product leader can now develop informed hypotheses on where trouble spots and / or areas of opportunity (e.g, sticky features) exist in your product.

As a purpose-built product analytics and engagement platform, PX enables you to conduct these analyses out-of-the-box. In addition, because the usage analytics is native to the application, it is seamless to build and target engagements based off of this data.

WalkMe Doesn’t Do User Analytics

WalkMe simply does not have this type of product analytics capability. As a result, you would have to purchase and integrate a separate analytics point-solution to fill this need. See below for a feature-by-feature look at common analytics capabilities and where PX plays:

WalkMe 2

Path analytics enables you to track the path traversed by your users and visualize which features are used in your application

You Need To Be Able to Measure The Impact of Walkthroughs and Guides, Not Just Interaction

The one type of analytics that WalkMe does do natively is engagement interaction. This means that WalkMe can measure whether a user or user segment interacted with a guide or other in-app engagement that has been launched – that is, did the users open it, did they click through, how many users saw it, etc.

However, as a product leader, what you actually care about is not interaction with the engagement, but whether interaction with the engagement drove adoption, retention, and increased sentiment. That is, was it actually effective in driving the outcomes you’re looking to influence? For example, it’s possible that users interacted heavily with a guide, but that interaction didn’t lead to increased adoption of the feature for which you’re trying to influence behavior.

Not only can Gainsight PX do engagement interaction analytics, it can also measure the true impact of an engagement on adoption and retention – the metrics that actually signal success. Did one particular guide drive better retention of users in the first 90 days vs. another? Which user groups were least influenced (and therefore may need a follow-up engagement)?

If your goal is to drive adoption and retention via engagements, you need more than just basic interaction analytics.

Personalized & Contextual Customer Onboarding and Product Walkthroughs

When it comes to driving adoption, no two users are exactly alike in terms of their lifecycle stage, product hangups, or use cases. As such, you need an optimized engagement strategy in which every user is receiving a highly personalized product engagement experience based on his or her needs; that is, your in-app guides and engagements shouldn’t be static. You should be able to target and deliver specific engagements and control engagement volume based off of a user’s role, account attributes, historical usage, and more. Some example use cases of this are:

  • Reference Salesforce data to present a personalized engagement: if a user is from an account that has purchased certain products or features (data found on the Salesforce account object), present only engagements that point to the value of those products / features.
  • Trigger engagements based on non-use: If a user has’t used a particular feature in the last 30 days, trigger an in-app dialog to describe the value; trigger an email to users who haven’t logged into the product at all in the last two weeks.
  • Throttle engagements based on volume: Nurture engagements until goal is completed: Serve the engagement more than once if the feature is not adopted and the guide was not completed
  • Drive adoption of a feature based on role, product purchased, and user behavior all together: These are more complex, but fairly common, use cases. For example, company X would like to drive adoption of the “Signature Workflow” module for accounts with the “business” package (found in SFDC) by targeting engagements to users that haven’t used it before
  • More complex: These users should be admins that used templates before and the volume of documents in their accounts needs to exceed X. (i.e, two usage patterns + role)
  • Once the Signature Workflow is adopted (verified by analytics) they then want to drive adoption for “templates”.

Because WalkMe doesn’t easily reference historical usage or integrate with Salesforce or other CRMs, the above use cases are not possible. WalkMe can only personalize based on session data and doesn’t have the concept of features; that is, you simply can’t personalize your engagements without additional coding.

With Gainsight PX, however, you have the data to trigger and drive highly contextualized engagements at scale – completely out-of-the-box. Put simply, PX features a real-time decision engine that is able to calculate dynamic criteria so fast that an engagement can be shown (or not) completely in the flow of the user’s experience — with absolutely no lag.

stop watch

Engagements That Don’t Slow Down Performance

Alternative solutions make a lot of network calls as the browser is loading the application. This can cause up to a 2-3 second slowdown in load times for pages, especially as you introduce more engagements. This severely impacts your end-user experience, particularly if your loadtimes are already longer that you’d like.

Gainsight PX is 100% server-side and, unlike alternative solutions, was built specifically for SaaS applications (versus websites). This means you can run as many engagements and permutations of engagements as you want to different, targeted audiences—without slowing your application down.

Drive a Cross-Channel Engagement Strategy

Gainsight PX’s seamless integration with the Gainsight Customer Cloud enables your customer-facing teams to take engagements to the next level. By leveraging Gainsight’s Journey Orchestrator capability, you can take a multi-channel approach to driving adoption. Specifically, in addition to in-app engagements to users, you can also layer in email and human outreach to Execs or others who may not be in your product on a day-to-day basis. This enables a holistic, programmatic, and strategic approach to customer engagement.

Ready to try Gainsight PX?

Sign up for a free trial of PX today and test out these capabilities and more for yourself.