CASE STUDIES
Learn more about how Intelemedia solutions solved complex business issues for our clients.
Industry – Nutraceuticals
Issue – The client’s direct TV media buys were marginally returning the required ROI. As a result, they were
unable to expand media buying and therefore increase revenues. With Intelemedia’s assistance, it was
determined a 1 to 3 percent increase in conversion rate would dramatically improve campaign
performance and generate a viable ongoing program.
Solution – Intelemedia knew there was no one magic bullet, but rather several well executed initiatives. The
following process was developed and executed:
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Create a predictive model of buyer and non-buyer attributes, based on historical campaign data.
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Develop a rating of every agent in each of the three call centers.
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In real-time production, score inbound callers to determine the likelihood of each caller to purchase the product.
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Route and queue each call according to score to the best performing agent available at that time.
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Provide clear information to identify which agent, media source and pricing options delivered the optimal ROI.
Results
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Within 30 days, conversion rates increased from 17% to 21%
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Call abandonment dropped from 25% to 16%
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Coastline Products reporting was provided to clearly identify media source, agent, and pricing option results, both in independent and all-inclusive views.
Coastline Products
Predictive Scoring for Direct Mail
Industry – Automotive Insurance Company
Monthly direct mailing campaigns were not delivering the positive ROI required to maintain the program. The cost associated with postage and mailing production did not cover the revenues generated.
Each month they sent 600,000 mail pieces from an internal database of previous policyholders.
Solution – With an effort to drive a positive ROI, the following steps were carried out:
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Predictive modeling was constructed to score mailing prospects on a scale of 1 to 10. In the end, two models were developed; one scoring lifetime value and one policy conversions from quotes.
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The objective was to reduce program costs by identifying a much smaller group of top prospects, mail to this group only and receive the same or substantially similar revenue compared to mailing the full list.
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The modeling utilized various data elements, which included attributes such as age and make of car, marital status, the presence of children, credit score, household income and other programmatically-selected characteristics based on correlations.
Results – After implementing the Intelemedia solution were were abe to change the size of themailing database to target only the top prospects, or approximately 40% of the entire list, eliminating 60% of the costs.
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