8 Best Practices to Maximize ROI from Predictive Analytics

8 Best Practices to Maximize ROI from Predictive Analytics

8 Best Practices to Maximize ROI from Predictive Analytics

Back in 2010, Forbes.com forecasted that something new and interesting called predictive analytics was emerging as a “game changer.” Well, fast forward a handful of years, and we can easily see that the prediction was an understatement – because predictive analytics hasn’t just changed the game for marketing professionals: it has fundamentally reinvented it. That’s because predictive analytics isn’t just a method of leveraging customer, prospect and other meaningful data to launch timely, micro-targeted communications and campaigns; on an even deeper level, it’s an engine that transcends marketing and is driving overall business strategy and vision. As Eric Siegel, Ph.D., chairman of the leading cross-vendor event for predictive analytics professionals Predictive Analytics World notes: “business is becoming a numbers game, and predictive analytics is the way to play it.” However, while many organizations are indeed playing this game quite well — such as Macy’s, Walmart, Netflix and eBay — at the current time, there are many others that aren’t as pleased with their results. This isn’t to say that they aren’t seeing gains in some areas (e.g. uptick in customer retention rates, improved engagement scores, better sales campaign numbers, etc.). Rather, it means that they aren’t reaping the full revenue and profit potential by maximizing their ROI from predictive analytics. What’s behind the underperformance? Typically, it’s that organizations of all sizes — from start-ups to enterprises – aren’t applying one, some, many or sometimes even all eight of these eight best practices: 1. Define A Clear Objective Organizations need to proactively define their objective when implementing a predictive analytics platform. Are you looking to: activate prospects, reactivate lapsed customers, increase customer lifetime value or donor value for non-profits? Having a clear objective will help marketing departments craft a more concise strategy and tactical plan going forward. 2. Validate Existing Data Sets Aside from capturing more data on customers, prospects and donors, organizations need to validate that their data is accurate and reliable. This is so when their database is full of unique contacts, and enriched with meaningful demographic, transactional, product/service and email marketing data on each contact. Click here for more information on ways marketers can capture and gather more data on their contacts. 3.

Read Also:
Where and How Will You Store All That Big Data?

 



HR & Workforce Analytics Summit 2017 San Francisco

19
Jun
2017
HR & Workforce Analytics Summit 2017 San Francisco

$200 off with code DATA200

Read Also:
Is Self Service Analytics The Key To True Data Democratization?

M.I.E. SUMMIT BERLIN 2017

20
Jun
2017
M.I.E. SUMMIT BERLIN 2017

15% off with code 7databe

Read Also:
Three Ways To Ensure Your Data Tells The Right Story

Sentiment Analysis Symposium

27
Jun
2017
Sentiment Analysis Symposium

15% off with code 7WDATA

Read Also:
Using Predictive Analytics To Better Manage Capacity In Healthcare

Data Analytics and Behavioural Science Applied to Retail and Consumer Markets

28
Jun
2017
Data Analytics and Behavioural Science Applied to Retail and Consumer Markets

15% off with code 7WDATA

Read Also:
7 Digital Analytics Trends that will Dominate in 2017

AI, Machine Learning and Sentiment Analysis Applied to Finance

28
Jun
2017
AI, Machine Learning and Sentiment Analysis Applied to Finance

15% off with code 7WDATA

Read Also:
Using graphs for intelligence analysis

Leave a Reply

Your email address will not be published. Required fields are marked *