Revenue growth starts with marketing data. And while we all have dashboards filled with forecasting metrics, you might ask yourself, “how exactly are those tools helping my team achieve better results?“
That is the million dollar question that we set out to explore in our latest episode of Revenue Science.
In this video series, we analyze scientific techniques that help transform marketing data into scalable, repeatable and optimizable results. This episode was all about improving business outcomes with prescriptive technology. Watch it here:
In my discussion with experts Sanjay Rajagopalan, Chief Design and Strategy Officer and Tao Liu, Vice President of Operations at Vianai, one point became exceedingly clear: predictive technology is far too passive to promote substantial revenue growth.
Why Marketers Need More Than Predictions
For decades, businesses have relied on predictive modeling to forecast revenue, but here’s the problem: predictive technologies are based on the assumption that GTM activities will always remain the same. In other words, they leave zero consideration for improvements to efficiency and effectiveness.
“Predictive analytics is getting the status quo and changing nothing,” says Rajagopalan. “You’re just predicting without really having any agency.” It’s the unfortunate truth.
Some companies even base their entire revenue strategy solely on predictive insights. When this happens, the only way to grow sales numbers is to cast a wider net and play a game of probability, or as some might say–‘throw spaghetti at the wall and see what sticks.’ However you put it, the static effect of using predictive technologies alone is expensive and time consuming.
Outcomes: A Marketing Game-Changer
Outcomes are part of prescriptive analytics and estimate how a KPI will change based on the adjustments made to the marketing strategy. Focusing on outcomes essentially creates a culture of continuous improvement across the entire revenue team.
“The way to think about affecting outcomes, is to say that outcomes are impacted by deliberate actions that are taken with an intent to drive value,” said Rajagopalan. “So examples of actions could be a sales call, running a marketing campaign–anything that the business does with the intent of improving an outcome, which then is directly connected to business value, is what you may say, a business action.”
The key word here is improvement. With outcomes, that forecast you saw is just a suggestion, and now you have the freedom to make changes that could have a real impact on revenue.
Taking a Prescriptive Approach
Instead of casting a wide net and spending marketing dollars to see what marketing actions work, prescriptive analytics allow us to understand why different customer segments behave in a specific way and more importantly, how to promote the responses we want from them.
“I think the first and a very important aspect is to help the decision maker understand what matters most to the customer’s behavior,” Liu says. “How exactly customers will react or what really triggers customers to change their behavior? Because every consumer or different group of the consumer, or customer, may have different triggers to change their behavior.”
A great example of this is looking at churned customers. If you simply target everyone who has churned with the same type of outreach you might cause more harm than doing nothing at all. Prescriptive analytics enable you to focus on churned customers who are more likely to change their mind as a result of specific action you take – like offering a discount or a free trial.
This approach allows you to save your marketing dollars and instead of taking one approach for your entire customer base, you can look at the data and take different actions for different groups of your customers. Or as Rajagopalan puts it, “getting the biggest bang for your buck”.
Making Better Decisions
The bottom line here is that predictions can’t change, but outcomes can. And prescriptive analytics give marketers a precise understanding of how to improve their strategies in real-time. Actions, outcomes, results – we know it’s easy to get a little bit of decision-paralysis when you’ve got a forecast to fix. If this feels all too familiar, reach out to one of Dealtale’s Revenue Science experts.
I hope you enjoyed this second episode of Revenue Science. Tune in for our next episode, where we talk about how to scale outcomes across the entire buyer’s journey!