Does Predictive Scoring Work if You’re Trying to Enter a New Market?

Cracking New MarketsThis is a question that often comes up in conversations with our prospects and customers. What happens when you want to push into a new market where you haven’t had a track record of success? Does predictive scoring offer any value? Or does it become a self-fulfilling prophecy that limits your potential?

The short answer is yes. Predictive Scoring can be extremely helpful in breaking into new markets. Here are some things to think about…

1. More in Common Than You Think — Even when you’re entering a new market, chances are that your new customers have a lot in common with your existing customers. Unlike typical approaches to scoring that that only use a handful of characteristics, Infer’s models use hundreds of signals. Therefore if there are only a handful of differences between your target customers, it often doesn’t matter much. The average scores for customers in the new segment might be lower at first, but probably not significantly lower.

2. Start Where the Ground Is Softest — The first step to breaking into a new vertical is creating a list of target accounts. That can be done inside Salesforce with a simple filtered list view. With Infer’s predictive scoring you get a relative ranking that tells reps at a glance where the ground is softest. Don’t worry about the absolute scores or comparing scores to other markets. What matters is finding the best place to break in.

3. Make the Commitment and See it Through — The biggest issue with breaking into a new market is often giving up too early because the wins don’t come easily and the revenue isn’t material in the early days. It’s really important that you have dedicated reps for your new initiative. Otherwise they’ll gravitate towards the easy money. If you can it is important to hire in pairs, so that you can breed competition and accelerate learnings. And don’t forget that early wins in a new market are doubly valuable as they not only build momentum, but provide additional data with which your models can become even better.

4. Manually Adjusting the Model — There are times when it makes sense to manually adjust the model to pick up on signals you intuitively know are important to focus on.This is a great example of blending the art of selling with the science. There are a couple of implementation paths you could take, so be sure to talk to Infer about what would make the most sense in your situation.

If you have questions, feel free to reach out. We’ve seen lots of different customers go down this path, and can help you figure out the best approach for your business.

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