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How to drive incremental business value through data and analytics

How to drive incremental business value through data and analytics

Retailers are driven every day to enhance the customer experience. As they continue to transform to meet shifting and higher consumer expectations, strive to capture a greater market share and aim for higher ROI returns, leveraging customer analytics and data will be an essential component of an effective retail marketing strategy.  Retailers can take advantage of the positive outlook and drive incremental business value through the following actions:

Connect the Data Dots…Analyze Off-line and Online Data  
Whether you execute digital, email, mobile, or direct mail campaigns, the ability to connect to customers in a relevant, personalized and targeted way starts with knowing who they are, what they want, and when they want it.  Whether working with “known knowns” or “known unknowns”, a key component to deliver customer clarity is high quality marketing data. However, it’s not enough to just have the data. You need to make the data actionable to gain immediate benefits and to have it fuel predictive analytics to more effectively plan a successful course of action in the future.

With data often residing in silos or not in a usable format, it can be challenging and time consuming to unify the data to create comprehensive customer profiles to generate actionable insight. Marketing organizations need to ensure there is a single system of record containing accurate, current and relevant data. By linking and analyzing customer activity data from various online and offline data sources and integrating third-party data (see “Complete the Picture” section below), retailers can:

  • Deliver personalized promotions and communications based on consumers’ purchase behaviors
  • Determine which channels and audience segments drove the highest performance
  • Use insights gained to simplify customers’ journey and convert browsers to buyers

Complete the Picture…Enhance Customer Data
Data enhancement plays a central role in today’s fast-paced, data-driven marketing landscape. By understanding multiple facets of a customer profile, retailers can tailor brand experiences that attract, engage and motivate customers to take predictable actions. Industry experts agree that segmenting customers based on attitudes and behaviors in addition to demographics is far more effective in tailoring value propositions and customer decision journeys than purely demographic variables alone.  In Forbes Insights report, “Reaching the Right Audience: How Brands are Using Audience Targeting in Digital Advertising,” 76% of senior marketing executives said that “Interest and Lifestyle” or psychographics is the most important targeting attribute for brand campaigns.

The rise of better-quality marketing data and advanced data analytics over the last few years has enabled a level of personalization that never existed before. By combining demographic, behavioral and psychological data about customers, retailers can leverage that data for better customer segmentation and personalize campaigns that resonate with their target audience.  In a 2016 InfoSys study, approximately 86% of consumers said personalization has at least some impact on the purchasing decision; and more than 30% of consumers want more personalization in their shopping experiences.

Use Analytics…Drive Business Value
Customer analytics and predictive models take full advantage of clean, accurate customer-related data enabling retailers to deliver a more meaningful, actionable customer engagement through:

  • Acquisition Clone Model: This flexible data-driven model answers the question, “Where can I best find new customers who will drive the greatest incremental sales?” Executing an acquisition strategy to grow your business with the right consumers starts with knowing who are your current “best” customers.  The model ranks prospects based on their probability of looking like your current best customers based on behavior, demographics, and attitudinal characteristics.  It provides the intelligence and analytics needed to make informed decisions to more of the right customers.

    Retailers can apply the Acquisition Clone Model to consumer names acquired from multiple sources to score and rank each prospect. The model focuses on targeting the highest value prospects yielding the most effective use of marketing dollars.

  • Customer Value Segmentation Analysis: Retailers can identify and segment customers into discrete clusters to target customers with the greatest current and potential value.  Allant has helped several retailers use Customer Value Segmentation, which includes RecencyFrequency, and Monetary (RFM) transaction history, to segment and rank customers into meaningful and measurable groups based on their value to the brand.  This segmentation supports customer migration and growth strategies focused on driving increased customer engagement frequency and higher average transaction value.  The outcome provides retailers with a solution that not only enables marketing and CRM strategies at the segment level, but also the ability to uniquely target and optimize at the campaign-level.

The key is translating data into intelligence that impacts profitable behavior change across all customer types—from the fiercely loyal to the bargain shopper.


    ABOUT THE AUTHOR
    Millie Whitley | Sr. Engagement Manager at Allant Group, LLC
    https://www.linkedin.com/in/millie-whitley-b486906/

    Millie Whitley
    Sr. Engagement Manager at Allant Group, LLC

    Millie is a results-driven leader solving complex business challenges with integrated technical and marketing strategies and solutions that increase profit, customer experiences, and company/team performance. She is the Sr. Engagement Manager at Allant Group, a data driven analytics firm.

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