You might be wondering what it’s like to actually use Tingono.
Unless you’ve seen our demo (which we also highly recommend), you might be asking yourself: what does an NRR boosting interface look like?
We’ve written a lot about customer success, revenue operations, and the future of AI. But, today, let’s jump into how Tingono works with an example.
With Tingono, it’s much simpler to be able to:
- “Predict” your customer's next move
- “Prepare” for the best course of action, and
- “Pursue” those actions.
To get started, let’s jump into “Predict”. (In a later post, we’ll also get into the "Prepare” and “Pursue” phases)
But what do we really mean when we talk about Tingono’s predictions?
We don’t just mean guessing what your customer's next move is. That's not very reliable of course.
Humans have trouble estimating an outcome based on more than 2-3 inputs.
For example, you might be able to figure out your customer’s likelihood to renew based on your email interaction with them, and maybe one other variable like how many times they login to your product.
But to be able to find a pattern based on all their product usage behavior, their spending history, and how they log support tickets, requires the use of serious data analytics.
That’s why it's much easier to lean on a robust AI platform like Tingono to do the heavy lifting for you.
Customer retention and lots of other things - All in the CSM workload
Let’s say you work as a Customer Success Manager (CSM) at a big company, such as Hubspot.
You are responsible for customer retention, finding upsell and cross-sell opportunities from your existing customer base.
The opportunities are often called Customer Success Qualified Leads (CSQLs).
These are demanding responsibilities.
Plus, depending on your company, CSMs typically quarterback all the interactions your customers have with the rest of the company, such as when to engage Sales Account Managers (AMs), when to involve support, or when to engage product/engineering teams.
Wouldn’t it be nice if CSMs had a crystal ball that predicted future churn and expansion outcomes?
That’s where Tingono predictions come in.
Going back to our example, as a CSM at Hubspot, you might be managing hundreds of accounts, along with the complexity of multiple products and tiers.
There’s Marketing Hub, Sales Hub, Operations Hub, and many others, depending on the customer.
Tingono first gives you a convenient snapshot of your top Risks (accounts with high churn likelihood) and Opportunities (accounts with high upsell and cross-sell potential).
Tingono’s early warning system predicts that Nike has a high likelihood of churning, and you want to learn more.
Luckily you’ve been informed well in advance.
With this prediction, you can work to mitigate the problems leading to churn.
First-class predictive analytics, without the first-class price tag
Many companies don’t have a data science team.
And even if they do, are these data scientists working on each account individually, telling CSMs when they need to try and upsell?
That just wouldn’t be sustainable.
Without more thoughtful data-driven predictions, many companies fall into using one-size-fits-all rules and playbooks.
For example, a rule might be if a customer hasn’t created more than 3 campaigns in your product in the last three months, you should attempt to call them.
Using rules assumes your customers are all the same and have the same reasons for declining product usage.
With Tingono, the calculations are done for you. Predictions are specific to each and every customer account. There’s no guesswork for CSMs to add to their already busy days.
They can see exactly what information they need, without the investment of their own personal data science team.
Tingono finds what is most relevant and essential for retaining and growing accounts and keeps you ahead of the curve.
Tingono is the natural next step for the most data-driven CS teams
So now you know when an account is likely to churn thanks to Tingono predictions.
That’s huge! It lets CSMs spend less time guessing and more time working on the most important part of a CSM’s job – building a relationship with your customer that promotes your offering's value.
The next step is figuring out why the customer is going to churn, like what behaviors and signals are contributing the most to their churn likelihood (the “Prepare” phase). Based on those signals, your team can act with efficiency (“Pursue”).
Stay tuned! More details on those phases to come in the next few weeks.
