Today shopping has transformed into an omni-channel experience integrating online to offline at multiple touch points. As a graduate student in Northwestern University's Integrated Marketing Communications (IMC) focusing on marketing analytics, I have found the following two articles insightful for shopper marketers. They respectively explain the big data utilization in shopper marketing and precision marketing analytics.
“Big data is a journey that every company must take to close the gap between the data that’s available to them, and the business insights they’re deriving from that data.” quoted from the article Shopper Marketing Filling the Cart with Big Data which draws the line form Lisa Klauser , president of shopper marketing at IN Marketing Services. According to the article, the integration of online activities and offline in-store shopping experiences creates tons of opportunities for brick-and-mortar marketers to track and measure the shoppers in more aspects than ever. By collecting and connecting more data variables together, marketers can more precisely detect the causality. Tracking the patterns in data is almost like keeping abreast of millions consumers from their online engagement to their offline purchase journey, while linking the patterns together could even lead to a map of specific decision-making process of each target segments. More importantly, technology enables marketers to track individual shoppers and connect multiple devices to in-store shopping. In other words, understanding data would help us to unveil the real identity of the consumers, estimate consumer lifetime value and take immediate actions.
More often than not, marketers use constant parameters regression (CPR) modeling to estimate advertising effectiveness, which is acceptable in revealing an overall effect which has been averaged out over time and different instance. In the article Precision Marketing Analytics: Working withTime-Varying Parameters from Accenture, the author compares the CPR modeling with the more advanced time-varying parameters (TVP) modeling. TVP modeling is able to discriminate the actual difference in advertising effectiveness at a granular level over time. Thus, it allows marketers to measure the real ROI of certain marketing activity separated from other actions across the time. As the example of a fictional FCMG company given in the article, using TVP model can especially help retailers and CPG brands attribute marketing efforts to real sales in a more accountable way considering the seasonality, geographic differences and other factors resulting in the volatility of this industry.
Connecting these two articles with my studies of marketing analytics at Northwestern, there are three actions you should consider in your next analytics project. They are as following:
1. Leap to insights - This not only requires the analyst to carefully examine the availability and quality of data, but also put the analysis in certain context and even from a personalized perspective. The leap from data to insights is usually propelled by finding the connections between consumers’ wills and their actual behaviors.
2. Deal with complexity. Simply average out the effect in analytics is dangerous in terms of both precise prediction and appropriate interpretation. Including time varying parameters is vital for marketers to discover the real unusual patterns.
3. Anchor analytics to strategy. Actually, the most effective marketing analytics is an eco-system creating the self-sufficient circle from data collection, personalized interaction with consumers through multiple channels, to measuring marketing effectiveness.
The transformation that is taking place in the CPG and retail industry is just as fast as the increase of data everyday. Always being innovative and analytical, professionals in shopper marketing would never let go of such a great opportunity of boosting their business to another level with data.
Amy Zhou is a marketing analyst who has experience in formulating stories for several CPG and retail brands through data analytics and market research. She is now pursuing her masters’ degree majoring in IMC at Medill Northwestern, with the concentrations in marketing analytics and digital marketing. She is strongly interested in work opportunities in related areas.
Connect with her on LinkedIn or Twitter @Amy__Zhou.
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