The future’s so bright, I gotta wear shades. 😎
We’re on the precipice of experiencing all the amazing benefits of integrating Artificial Intelligence (AI) and Machine Learning (ML) into our day-to-day business.
I’m like a kid the night before Christmas. I can hardly wait. I’m so excited for it!
So with this excitement built up, I want to talk about the future of GTM tools in part 4 of this series.
In Parts 1, 2, and 3 of this series, I went over the 360-degree customer view, predictions, orchestration, and automation.
But now you might be asking, how does this all fit together? And for what?
The problem with one-size-fits-all GTM tools
Today, most go-to-market (GTM) tools fall into one of two categories: 1) top-of-funnel growth or 2) dashboard overview.
The top-of-funnel growth tools (like CRMs for PLG) don’t dive deep into existing customer data because they focus on the beginning of the customer journey and conversion. So, they simply don’t need to.
The dashboard overview tools (like CS Platforms) take in event-based data and provide a 360-degree view of existing customers.
Both of these tools are unfortunately rules-based systems that simply help you formalize a process for a specific GTM function.
For instance, a top-of-funnel tool can help AEs formalize selling in a PLG world. And the dashboard overview helps CSMs formalize their CS workflow.
In this sense, they both suffer from what I describe as the “center of excellence” fallacy.
They are built on the premise that if each function in your company performs their roles really well, revenue has to follow.
Unfortunately, this incorrectly assumes that all customers are the same and the market is a static environment.
To expand revenue, customize solutions for each customer
We know these things just aren’t true. The market is a dynamic place. And each customer is unique.
This demands a customized solution for each customer. Ideally, this solution would adjust with every new piece of information about the customer. As well as new market information.
A data-driven approach partnered with customer business intelligence, like we’re pioneering at Tingono, delivers this. And it directly ties every action back to revenue.
The difference is night and day.
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A one-size-fits-all GTM tool might use a net performer score (NPS) or feature usage to assess a customer's likelihood of staying with you…and then provide a follow-up playbook.
Whereas, Tingono utilizes all customer data points to tell you if a high NPS is relevant at all. And if it is relevant, what the best next action is to increase revenue.
Tingono’s ML-driven platform makes it easy to increase recurring revenue from existing customers
This I believe is the holy grail around which every SaaS business will align in the future.
We can’t lose out on the opportunity that integrating ML and AI into our business provides.
Advances in technology have enabled us to determine with precision what really matters to your customer, how to deliver it, and when to deliver it.
This is a future that’s free of generic emails, BDR calls that are fact-finding missions, and toothless CS QBRs.
This is a future where companies can anticipate what their customers really want and are able to proactively offer it!
Check out the other 3 parts of the series:
