The customer cheat sheet is the first of the many Generative AI capabilities that Gainsight plans to deliver over the next few months. As you leverage and enable your users on Cheat Sheet, here are a few things to consider:
Value:
- Executive summary on what’s going with the account: If you are an exec, and If I were to ask you what are your top pet peeves, chances are that I will hear about those last minute customer meetings where you don’t get enough prep or the meeting prep is inconsistent across different teams and individuals. And if you are a CSM or any customer facing team member, you probably do not enjoy writing and briefing your executives for those customer meetings which sometimes takes hours. What customer cheat sheet would provide is an instant, high quality summary that leverages Generative AI to create customer summary from unstructured and structured data including meeting notes in a quick digestible format. This summary also leverages RLHF (Reinforcement Learning from Human Feedback) by giving the users the option to provide feedback on each point and also enter their own notes. As this functionality is already in Beta, we are leveraging this in our own CS org and found that this saves 30-45 minutes per meeting prep. So even if you have 10 such meetings per week, you are saving 300 mins straight by using this feature.
The consumers of these features are not the current CSMs associated with the customer but the rest of the organization such as your execs, Account Managers, Product and Services team. If your CSM has left the organization, executive summary can start as a reference point for the new CSM to understand what’s going on with the customer. - Customer Cheat Sheet will also reveal gaps in your current customer relationships: If your CSMs are not entering the notes correctly or copiously, your exec summary will be inaccurate and sparse. When your CSMs are not talking about strategic priorities, that section will be empty in the customer cheat sheet. If the AI is not able to gather right info from the notes and other unstructured data, chances are a) Either the notes are not being logged/recorded accurately or b)CSMs are not having the right conversations with the customer or c)Both a and b. So although you may have to face the uncomfortable truth that certain customers are being under-served or that the CSMs not being diligent about logging key customer goals or information, you will have the opportunity to course correct rather than finding about this process/personnel gap after the customer is at risk. As a CS leader, I often use the customer cheat sheet and the quality of customer cheat sheet gives me a good indication of how much work has gone into this customer (or not).
- When you make it easy, you make it accessible: There is a second order benefit from using cheat sheets. When meeting prep is no longer a drag both for a CSM to product and an exec to consume, guess what? Your execs will meet your customers more often. It will be far more easier and far less friction towards making sure that the you have right stakeholder alignment with your customers in place.
Enablement and Change Management:
- What's unseen often goes unremembered: Make sure that the Customer Cheat Sheet is at the front and center of your 360 page as soon as you land on it. It should NOT require 2-3 scrolls to reach the customer cheat sheet section. Since it is a new functionality, your users and execs have not yet developed the muscle to look for it.
- Set your users up for success: Make sure that you enable your users to refresh the summary to reveal the latest and the greatest.
- You reap what you sow in data: Like any AI or ML model, the output or summary is as good as the dataset that it is trained on. If the data is sparse, the summary will not be useful either. If the CSMs or other team members are not filling in rich meeting notes in Gainsight, the customer summary will hardly be accurate.
What’s next:
Here are some ideas where I hope that we can evolve Customer Cheat Sheet once it gets more widely adopted in your organization. Note that these are only ideas from a pov of CS leaders and does not reflect our current product AI roadmap:
- Meta trends: When you have customer summaries generated, used and enriched (with the right input, also see below), you just don’t have customer level summaries. You can also generate mega summaries on the general trends of a business or a specific segment. So an example would be that I can ask this Mega Cheat Sheet about trends in my ed tech customers and it can reveal specific insights based on what the individual customer cheat sheets of these customers. Imagine looking at thousands of such customers and coming up with insights and trends across the business such as ‘It takes approximately 8 weeks more to onboard a ed tech customer versus the rest of our customer base’ or ‘In general, our security space customers are likely to raise 30% more support tickets in a month than our non-security customers’. Imagine what you can do with these two data points! You can come up a specific onboarding offering for your ed tech customers to remove the 8 week delay or you can try to sell your premium support package to a security customer. The possibilities are endless!
- Make summarization easier: Pushing AI generated meeting notes, action items and follow ups right from the customer calls to the Timeline. This also solves to some extent the issue of bad quality meeting notes (I still believe that there should be some accountability from the CSMs to ensure that the standard of the notes are not lacking and incomplete).
Tell me more about what gets you excited about this cool courtship between AI and CS!
