In the dynamic landscape of SaaS enterprise solutions, losing a champion within an account can feel like a heavy blow.
The relationship you may have built with them may have taken years to get to this point.
And then learning that something has changed, whether that’s a job change, a team restructuring, or some combination of factors is tough to hear.
However, this setback doesn't have to spell the end.
By harnessing the power of data-driven strategies, especially ones using AI, businesses can transform adversity into opportunity, ensuring that the account remains in good hands.
You can still keep accounts even if your main advocate has left- you just have to be mindful of how you go about it.
Let's examine the art of retaining a SaaS enterprise account despite losing your champion, all while making the most of valuable insights.
Losing a champion within a SaaS enterprise account can disrupt the balance of the client-provider relationship.
This individual often holds deep knowledge of the product and was instrumental in the adoption process.
They also serve as a vocal advocate within their organization.
They might be the go-to person for questions about the product- so when one of their peers has a question, and they're no longer there, that peer seemingly has no place to turn.
And they may not have any sort of relationship or knowledge about the product provider- like the CSM or account manager for it.
The departure of such a champion can lead to decreased engagement, slowed progress, and even account churn.
So one of the first things to do when you learn that a champion has left, is to evaluate how that champion utilized the relationship.
What your relationship with this client going forward will look like will jump off from this point.
You can start with these questions:
Did they come to you for every question, big and small?
Did they normally attend QBR's?
How did they advocate for the product internally?
Then, once you have that broader overlook of the account, you can get into the nitty-gritty.
Customer journey data holds the key to uncovering insights that can help you mitigate the risks associated with losing a champion.
By analyzing usage patterns, adoption rates, and customer feedback, you can find areas of concern and create tailored strategies to fix them.
Fully grasping your customer journey data as it comes in can better help you predict how your customers will behave down the line. Rather than trying to band-aid fixes for accounts, using data can help you mitigate risks earlier.
Armed with data-powered insights, it's time to provide tailored support and training to bridge the gap left by the departed champion.
With AI tools to help you, you can better use these insights to retain the account longer.
When these practices are instilled for this account, and for one's going forward, you can get away from leaning heavily on “relationship” based accounts, and use the data you have to better understand your customers.
Data can give you the superpowers you need to keep customers longer, without needing to entirely rely on feelings or how relationships "seem" to be.
When customer data is used from the start, you don’t necessarily need to lean on having an internal champion.
It becomes more of a “nice to have” rather than a need.
The data gives you the information you need.
Rather than assuming an account is good because your champion said everything was fine, you can instead dig into their journey data, and figure out if they’re truly getting the most from the product.
So while losing a champion right now may cause some unsettling feelings, really, what it can do is kick start a better motion of using data!
Tingono makes keeping accounts simple- it does the heavy lifting of understanding your customer for you.
We know that trying to figure out x amount of signals and conversations and various other data points can be a challenge.
And we know that we can’t use the same playbook for every customer, or every situation.
But, with the power of AI, we can get better insights that are grounded in data, for each account.
We can aggregate all of those signals without a data science team.
Even without a champion, we can still have an understanding of what our customer needs the most, what features they’re suited for, and we can mitigate churn before it surprises us.
Curious about how Tingono can help you get away from reliance on champions, and get into the heavy lifting of data using AI?