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Case Studies
Increasing Product Value with site+1
Industry
Financial Services
Challenge
A leading financial services provider offered a series of credit cards targeted
towards small to medium sized businesses. The company has nine products which
they could display on both the site’s Home Page and the Card Application
Page, but only wanted to display the three products that are most relevant to
the user and have the highest probability for conversion. For this program, [x+1]
not only optimized for acquisition, but also for value; each card has a different
value to the company (some cards enjoy higher spend rates than others), so the
optimization process balances the serving of cards that have the highest probability
of conversion and highest net present values.
Solution
Segment consumers based on behavior and provide more targeted,
relevant offers.
[x+1] understood that each consumer who came to the site was different, and therefore
used site+1, a solution that screens audiences and enables impressions to be
targeted towards the audience most likely to convert. The same solution that
drove lift by segmenting visitors in order to maximize card applications, site+1 was now used with a different optimization goal: maximizing the dollar value
generated. The expected value for each audience group was calculated as the response
rate for that group multiplied by its net present value (NPV).
Utilizing data
gathered from POE™, [x+1]’s continuous, audience-based, predictive
marketing platform that uses automated, real-time decision-making to help marketers
make actionable decisions, [x+1] used the company’s NPV data on each of
the cards to optimize the offers shown to each segment, presenting a targeted
offer that would generate the highest likely revenue.
Measures and Results
The optimized offers increased product value by over 100%!
The company was also
able to gain a better understanding of how valuable each of their many cards
were by evaluating success using different metrics than they had used in the
past. Instead of simply tracking card applications and lift in application rate,
they could calculate an expected value for impressions shown to each audience
cluster, and readily measure the ROI of their optimization program on an ongoing
basis.
Additionally, [x+1] was able to provide the company with valuable customer
behavior insights to help them with their future marketing strategies. |
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