Making the Case for Predictive Marketing and Sales

Many companies out there are asking, what can predictive do for me? A recent webinar with SiriusDecisions Sr. Research Director Kerry Cunningham, Infer Sr. Director of Product Marketing Sean Zinsmeister, and Lattice Engines VP of Product Marketing Nipul Chokshi highlighted the top use cases where predictive analytics are making a powerful impact on revenue funnels.

Let’s break down some different use cases where predictive marketing and sales can help companies improve the efficiency of their revenue funnel:

  1. Too many leads: The issue of having an overwhelming number of leads in your demand waterfall is a top issue for fast-growing organizations with a freemium business model. With predictive analytics, marketers get a complete view of the customer, and can pass the highest value leads over to sales, while using a precise customer profile to create customized nurtures for those not yet ready to buy. This also enables sales to prioritize their leads based on the predictive score and attributes of a lead or account. By knowing who to call first, sales reps are building an accurate pipeline and avoiding cold calls to prospects that will never convert.
  2. Too few leads: Another top use case for predictive is averting the scarce leads scenario. Most companies know their general market universe, but have no idea which companies exist in that space, and don’t have contacts for those accounts. Predictive marketing solutions help companies get a complete view of the B2B customer world, so they understand who their ideal buyer is, and then can go find new prospects that fit that buyer profile. In this way they can smartly grow their database by only adding high-propsensity buyers, rather than random names from a purchased list.
  3. Poor conversion: This is yet another huge pain point that predictive analytics alleviates. By using predictive marketing and sales to create a complete customer persona, marketers are able to take that data and create hyper-targeted segments and orchestrate personalized marketing across multi-channels, including through the sales team. This kind of scalable, targeted outreach ensures that conversion rates increase along with the revenue pipeline.

While these remain the top use cases for predictive, there is always room for more! Using predictive helps bridge the divide between sales and marketing, supports operationalizing  campaigns across your CRM and MAP systems, and enhances the segmentation capabilities of teams. At the end of the day, predictive analytics is about using data to get a complete view of your customer, and letting the technology surface relationships that cannot be seen with the naked eye.

If you’d like to learn how to get started and understand the best ways to measure success, check out the webinar!

Written by

Daniela Ulloa
September 21, 2016

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