Customer retention strategy for your B2B SaaS business: Part II

This is the second of a two-part series on building a customer retention strategy for your B2B SaaS business. Click here to view Part I if you missed it.

2. Once you’ve begun tracking events, determine which ones are most important

(continued from Part I) If there are different use cases for your SaaS platform, it is also important to consider that event importances may differ for these different use cases. For example, if your two primary customer cohorts are B2B SaaS companies and Nonprofit charities, it is likely that these two customer segments have very different use patterns for the software (considering that the B2B SaaS company is run for profit, and the charity is not).

Considering event importance in the context of a HR SaaS tool, it would be more important for the HR manager to add employees to the tool, before they add their own personal profile picture - whilst adding a profile picture may definitely be a sign of positive user engagement, it would correlate more weakly to successful use of the tool - the main functions (approving vacation days or sick leave) cannot be completed without adding employees first. This event-ordering could be done with a number of different approaches:

  • A basic way would be to take the subjective opinions from the team of sales agents, based on their client observations. This would be relatively effective on a high level, as they will at least know what are the main features used by customers through their regular interactions. However, there will always be some error or ambiguity associated with this method.
  • Kicking it up a notch might be to analyze tracked event data that was mentioned in Point 1 above, if it has been tracked, and determine what features are used most frequently by your users. However, not everyone (myself included, ahem, guilty) is a data analyst - this can be done in-house, but it is time consuming, and user behavioural patterns can change over time. In addition, software features can always be added or changed, so this would need to be re-examined on a somewhat regular basis to maintain accuracy of the customer journey model.
  • So, even better would be to synchronize data with a platform like Traitly, will uses powerful AI algorithms to determine what are the most important events along the customer journey, based on your past successful user interaction with your software. The event data will also be continuously re-evaluated, taking into account any new users who signed up and what actions made them successful users.

3. Use this data to determine those users who are most likely to churn

Now that you have identified what events are most important for maximizing your user lifetime values, it is best to use this data to determine what paying users are most likely to churn - based on which clients are not interacting with certain key features and their overall level of activity, more generally. This can be done in a number of ways, including, but not limited to:

  • having account managers manually sift through accounts to see what clients are best to contact - rather inefficient, and time consuming, and personal subjectivity may be a problem here, but hey we are all human. There may be hundreds or even thousands of these accounts, and the monotonous nature of this course of action is likely to lead to errors by the account managers (not really their fault when there are more efficient ways to do this).
  • build an in-house model to determine those at risk of churn - a step up, but still time consuming for 1) developers, whose time would probably best be spent optimizing your product and fixing bugs that affect user engagement, and for 2) business intelligence, of whom could deliver more value by spending their time analyzing external business trends and opportunities, rather than building in-house tools. An in-house model will also have to be modified manually as business trends change, and new features are added, further impinging on developers and analysts time - and this is almost inevitable, as things change in the SaaS space very quickly - it’s a vicious circle!
  • along with determining the key events, as mentioned above in Point 2, Traitly incorporates a built-in retention score strategy, scoring each customer from 0 to 100%. This scoring system separates your customers into four segments: very likely to churn (75-100%), likely to churn (50-75%), unlikely to churn (25-50%), and very unlikely to churn (0-25%). You can then employ different strategies based on the bucket each customer falls into (more on this in Point 4 below). This can be determined within minutes of syncing data with Traitly, so you know what events are most important and who to contact almost instantly, saving weeks of potential in-house work by software developers and analysts.

4. Reach out to these customers at risk of churn

Now that the users who are at risk have been identified, it’s clear who needs to be contacted. You don’t have to blindly contact everyone hoping that you may or may not have saved a customer from churning. Because event data has been tracked, and you know what features your at-risk customers are and are not engaging with.

It will be very easy to send targeted and personalized emails to your customers, whether sent manually by account managers or in an automated manner.

As discussed in Point 3 above, Traitly will segment each customer based on their churn likelihood. When reaching out to customers to contact, a basic approach for each segment could be:

  • Very likely to churn (75-100%): Evaluate the customer’s account. Analyze how their activity differs to successful customers. Then, pick up the phone and call or send a personalized email. The conversation should be geared around getting the customer engaged with your product. Recommend basic next-actions which will enable them to begin getting value from it. It may be the case that some customers in this segment will churn no matter what you do to help.
  • Likely to churn (50-75%): It’s likely that customers who fall into this bucket have the problem your product solves but are unsure how to get the most out of your product. Your focus should be on product education.
  • On the other hand, those who are unlikely to churn (25-50%) and very unlikely to churn (0-25%), probably love your software and would happily rave to others about how great you are. They have potential to be product champions. However, just because these customers are unlikely to churn, it doesn’t mean that they have to be completely ignored: take advantage of the customers who fall into these segments - ask them to leave reviews on sites such as TrustPilot, offer them referral incentives (as successful users, they are likely to recommend to friends), and consider their product feedback seriously.

With Traitly, if you want to take a more automated approach to retention, you can export dynamic segments of customers (customer cohorts) to your CRM softwares (e.g. Hubspot) or Social Media platforms (Facebook, Twitter). You can use Traitly’s dynamic segments to send targeted, personalized messages and adverts - minimizing churn and maximizing retained revenue. You can also export segments of users based on what events they have or have not completed, for a more granular approach. We have other blogs that explain this information in more detail.

For those who have not knowledgeable of retention, the above at least provides some key steps in getting started. If the steps above may take a long time to implement, it’s not the end of the world! Once your key events have been identified and logged, Traitly can help you with the rest.

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James Moran

James Moran

James is the Customer Success Lead at Traitly. Previously, he worked at xSellco, a fast-growing SaaS company. Given his engineering background, he takes analytical approaches toward customer success.

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Customer retention strategy for your B2B SaaS business: Part II
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