Who wouldn’t like to know the future?
When the predictive analytics craze first hit the B2B scene, some Sales and Marketing people were led to believe it could enable them to do precisely that: plug in a predictive scoring model and — viola! — they’d know exactly which prospects would convert, and which were a waste of time and energy. That way, they’d be able to effectively target only the right audiences, drastically improving their conversion rates and the ROI of their campaigns.
But things were hardly that simple. Businesses began to realize fairly quickly that “predictive” alone was of little use, particularly in the long-term. Specifically, most predictive scoring platforms built their models largely, if not entirely, on the existing first-party data within their customer’s CRMs or Marketing Automation Platforms. When you consider how much of the average B2B Marketing or Sales database is clogged with incomplete, incorrect or outdated data — and how rapidly even “good” data tends to go out of date — it’s no wonder many vendors failed to deliver on their ambitious promises.
The cardinal rule with any AI solution like predictive modeling is that the quality of the results is only as good as the data it’s using. This is true whether you’re using the most basic machine-learning technology, or the most advanced AI known to man. If the data’s bad, then it’s “garbage in, garbage out.”
On the other hand, if the data is good — accurate, up-to-date, and actionable — the sky’s the limit.
Predictive Intelligence + Data = Audience-Centric Marketing
When Sovos Compliance first went looking for a predictive solution, their objective was to finally make sense of their messy data, and enable Marketing to run personalized, audience-centric campaigns.
But they soon realized that stand-alone, “traditional” predictive platforms couldn’t provide an effective solution, since they’d be building predictive models using the same problematic database, filled with missing, incorrect and incomplete account data, non-target accounts/contacts, duplicate records and multiple data silos.
“We realized we needed to clean up outdated data before we did any actual modeling,” Sovos Marketing Operations Manager Jon Jagelsky explained.
Using Leadspace’s Audience Management Platform — which combines comprehensive, real-time data enrichment and outbound prospecting with advanced predictive modeling — Sovos were able to increase their win rate by 55%.
Watch — How Leadspace Audience Modeling Enables Highly-Personalized Marketing Campaigns:
For Jon and his team, this was a game-changer: “The Leadspace methodology really works – there isn’t any other solution out there that offers the three-in-one solution Leadspace has.”
To learn more about Sovos’s success with predictive modeling, including significant increases in win rates, conversions and Sales pipeline quality, read the full case study:
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