September 16, 2020

Bringing a New Product To Market: Bridging the Divide Between Insights and Activation Through Data Strategy

How Nationwide designed a debt-reduction product with differentiated market features.

Bringing a New Product To Market: Bridging the Divide Between Insights and Activation Through Data Strategy
Dave Stewart

by Dave Stewart

Vice President at ENGINE

Research Challenge:

Nationwide Innovation works to identify unmet needs in the marketplace and create solutions and products to fulfill those needs for consumers. In an effort to better meet the needs of financially distressed consumers, Nationwide looked to design a product with differentiated features, that will lead to total debt reduction and ultimate less consumer stress. Essentially, Nationwide wanted to understand the following:

  • Is “Phoenix” a go or no-go product?
  • What is the profile of those interested in the concept?
  • How do we reach the desired target? i.e. what is the path-to-purchase?

 

There were three main challenges to this project:

  1. The concept is specifically targeted to reduce credit card debt, which can be challenging to get consumers to “open up” about their debt and how they manage it. Conducting an anonymous, online survey helped alleviate much of this concern.
  2. Given that we were partnering with an innovation team we needed to match their pace and iterative approach to new product development. Therefore, an agile and iterative solution was mandatory.
  3. Lastly, for the product to succeed, the innovation marketing team needed to know who to precisely target. A well-defined target audience creation was key to success.

 

Solution:

To address the business objective a multi-phased agile and iterative research solution was created.

Phase 1: Concept Assessment & Refinement (quantitative)

  • Confirming the appeal of the broader concept and determining the most intriguing features and benefits were the main objectives of this initial phase
  • Method: <10-minute online concept test, n=1,000 gen pop credit card holders
  • The test included standard concept KPIs (appeal, uniqueness, likelihood to download, etc.) with a MaxDiff exercise to determine key benefits and features
  • Resulting in the data and insights for a decision to move forward and develop a final concept

 

Phase 2.1: Concept Confirmation & Path to Purchase (quantitative)

  • Once a more finalized concept was created following Phase 1, ENGINE recommended a second concept test to confirm appeal and measure other KPIs. Additionally, we need to further explore how consumers deal with debt and what resources they are aware of and use (path-to-purchase)
  • Method: ~15-minute online survey, n=1,000 gen pop credit cardholders
  • Phase 2.1 objectives were to:
    • Test and confirm the appeal of the refined financial wellness platform
    • Identify product enthusiasts (based on appeal and likelihood to download)
    • Understand and ultimately determine believed path-to-purchase

 

Phase 2.2: Audience Profiling & Creation (Data enhancement)

  • We deterministically matched (i.e. 1:1 match) online behavior with intentions, i.e. the surveyed consumers who showed a positive reaction to the concept
  • Via machine learning, we used this match to identify digital signals that are most indicative of appeal and likelihood to download (2 main KPIs)
  • These signals were scaled to the wild, providing Nationwide with an audience of ‘likely product adopters’ that could be targeted programmatically across digital channels

 

Results:

Our client was able to present findings to senior-level executives, including Nationwide’s Chief Innovation Officer. The insights provided them with the “ammunition” to secure funding to move forward with the development of “Phoenix”. The insights further guided the campaign strategy to promote demand for the new product, enabling Nationwide to effectively target highly likely product adopters.

 

insights that workpath to purchasepurchase intentquantitative researchsurveys

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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.

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