Improve Your Marketing Campaigns’ Ability to Target with Predictive Analytics
Thanks to technology, marketing is becoming an increasingly exact science. Predictive analytics is among a growing number of measured activities that can help enhance a marketing campaign’s odds of success. It blends statistics, AI and machine learning with historic and transactional data to analyze buying patterns. Let’s explore the opportunities.
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SPOT THOSE MOST LIKELY TO RESPOND TO YOUR MARKETING SALVOS
Predictive analytics takes historical data -- marketing’s Holy Grail – to the next level, making for more accurate forecasting. Predictive analytics works by enabling marketers to score or rate leads based on the leads’ likely willingness to purchase. A study by the Aberdeen Group revealed those using predictive analytics doubled their likelihood of pinpointing high-value customers and marketing the right offer. In this way, you can laser focus efforts on those most likely to convert.
We analyze predictive analytics’ ability to blend data, statistics, machine learning, AI and other tools, delivering campaigns based on correct customer behavior predictions.
A CMO Survey learned that over the next three years, the percentage of marketing budgets allocated to analytics will skyrocket from 5.8 to 17.3 percent, a 198 percent hike.
Read Predictive Analytics for Marketers: Using Data Mining for Business Advantage, by Barry Leventhal.
Not long ago, predictive analytics technology remained beyond the financial reach of all but the best-heeled companies. That's no longer true. AI-powered marketing tools such as digital knowledge management and natural language generation platforms and advanced image recognition systems, are now affordable, enabling many more companies to profit from their use.
Email or call us at 708-246-4211 to learn how predictive analytics can help your company gain a marketing edge on its competitors.
DO A BETTER JOB OF RETAINING CUSTOMERS AND AVOIDING CHURN
Sprint once analyzed customer data in a manual and very cumbersome way. Then the mobile carrier began leveraging an AI-enabled algorithm to spot the customers most likely to leave the company. Once it identifies those people, Sprint can use the same science to predict when they will leave, what will make them stay and deliver that offer just before they would leave. Since switching to predictive analytics through AI, Sprint reduced customer churn by 10 % and earned higher marks from patrons.
Scoring leads and reducing churn are two of the big ways companies can use predictive analytics to optimize their marketing efforts. Here are 3 more key areas where predictive analytics can boost your bottom line:
Upselling and cross-selling let companies gain incremental revenue from existing customers. Predictive analytics' insights into the customer journey help marketers know which customers can be upsold or cross-sold, and what will appeal to them.
Customer Lifetime Value (CLV) identifies the extent of the value a customer will provide a company over the relationship's lifetime. Predictive analytics can deliver actionable insights enabling marketers to make data-driven estimates of CLV.
Its ability to track customers' purchasing data back to their first experience with the brand means predictive analytics can help companies gain a better handle on ROI.