Predictive analytic power

Patrick Surry's picture

Predictive analytics is a highly powerful business tool that in recent years has been increasingly embraced by marketers and utilized in a variety of marketing applications. Here at Portrait, we have witnessed how predictive analytics software has helped our customers to deliver more efficient marketing campaigns and generate substantial incremental revenues.

Earlier this month, Forrester’s James Kobielus, author of the inaugural Forrester™ Wave: Predictive Analytics and Data Mining Solutions, Q1 2010 research report, presented a webinar discussing best practices in predictive analytics and data mining. Key learning points from the webinar included:

  • Using predictive analytics to target marketing budgets more effectively
  • Optimizing every contact you have with your customers
  • Uncovering best practices for customer analytics within multi-channel campaign management

Uplift for Cost Reduction

Targeting marketing budgets more effectively is a key goal for many corporations that integrate analytics into their interaction strategies. Uplift modeling, the focus of last year’s Predictive Analytics World Conferenceis a proven and effective way for companies to reduce marketing budgets by segmenting their audiences.

Uplift modeling categorizes customers based on their predicted behavior in response to a marketing campaign. With uplift, your audience is divided into four segments:

  • Sure Things - those who are likely to buy (or renew) regardless of marketing
  • Lost Causes – those who will never buy, regardless of marketing
  • Persuadables - those who are likely to buy (or renew) only when marketed to
  • Sleeping Dogs – those who will buy only if not contacted

By using this approach, marketers can ensure that their efforts are focused only on the “Persuadables,” while avoiding wasting time and money on “Sure Things” and “Lost Causes” or annoying potential “Sleeping Dogs.”

Uplift modeling is an effective approach to cost reduction for two reasons: it reduces money spent on outreach by singling out only the best individuals for marketers to approach, and it reduces cost of fulfillment, as it prevents marketers from giving away special offers or incentives to customers who were going to buy or renew anyway, at full price.

That’s Just the Beginning

Predictive analytics applications are not only restricted to uplift, but this is certainly an interesting and effective use that has produced real, measurable results for many companies.In addition to its cost saving abilities, predictive analytics also helps companies to maximize up-sell and cross-sell opportunities, improve customers’ experiences and boost overall customer loyalty. But those are all blog topics for another day! Stay tuned.

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