By John McIndoe
Recently I was searching online for a new “smart” coffee maker after realizing it was finally time to upgrade my 15-year-old pot. After reading multiple consumer reviews on different websites, I decided on a brand and model to purchase. Before I could add the item to my online basket and check out, my kids jumped on my lap to tell me it was time for dinner, so I stopped my search.
The next time I logged onto my computer, I had forgotten all about my hunt for a coffee maker. Instead, I ended up on two retailers’ websites searching for other items. Retailer A’s web advertisements featured fall’s trendiest sweaters. It was nearly 80 degrees outside so I didn’t pay much attention. Retailer B, however, was advertising the same coffee maker from my earlier search and highlighted a coupon code that would provide free shipping. It was clear to me that, unlike Retailer A, Retailer B had personalized their marketing. Thanks to big data, Retailer B could address my specific needs. I now wake up to freshly brewed java every morning from my new coffee maker, and Retailer B made a sale that otherwise may not have happened.
Why Do We Need Personalization?
It is no secret that consumers are more demanding. With all the messages coming at them each day, they pay more attention to the ones that are personalized to their specific needs. Media, manufacturers and retailers are frantically trying to catch up, and the research and insights industry is working at a breakneck pace to help. Mastering big data is on the agenda of most major companies, but it should be the highest priority for ALL companies.
E-commerce currently accounts for 11 percent of sales and is growing at more than 15 percent per year, every year. It is set to grow from $11 billion in 2015 to $55 billion by 2020. As more consumers divide their shopping between brick-and-mortar and online, it is imperative that brands and retailers implement and analyze big data on all fronts (online, media, in-store) or else dollars will be lost.
Common Personalization Pitfalls
To achieve true personalization, you must understand shopper dynamics in a wide range of situations. How do shopping patterns change when it rains, when traffic is heavy, or when it’s hot outside? A company that under-invests in data will not be able to get a clear and accurate 360-view of its target consumer, which leads to inaccurate targeting – similar to Retailer A above.
Out-of-sync execution is also a factor to consider when targeting consumers. Strategies that activate shoppers must aggressively motivate them. For example, offering a $.50 coupon to an individual with a $100,000+ income likely won’t incentivize them to make a purchase. It’s also vital that the organization can pivot quickly; if you build a personalization capability that provides rapid insights, your organization must be able to rapidly follow through.
Ultimately, the shopper is the boss and all strategies and campaigns must be constructed to address their needs. With that in mind, the program is only as strong as the weakest link. Every element of a personalization program should reinforce the other facts. If the planning and targeting strategies are superior, but the activation campaign is weak, the entire program may fail.
For retailers and marketers that are unsure of how to leverage big data or get the most out of the insights they already have, there are some specific steps you can take to win in personalization.
Seven Steps for Successful Personalization
1) Advanced technology platform. Retailers and marketers need access to an advanced technology platform developed specifically for integrating enormous quantities of different data types such as point of sale (POS), loyalty and social, in different formats and with multiple analytics capabilities. Ideally, the platform is cloud-based so teams can access the information anywhere. A primary goal of the platform should be to democratize data access and generate results in near real-time to facilitate decision-making.
2) Insights. With the platform in place, teams can gain insights to understand consumer purchase behavior at the individual level by leveraging frequently updated loyalty card information and media viewing habits, including TV, display, video, social and mobile.
3) Planning. These new insights identify high-value shopper groups (this doesn’t necessarily mean shoppers with the largest budgets) that can be targeted. Plan new product introductions that appeal to these groups if you’re a manufacturer. Update store layouts and planograms if you’re a retailer. And refocus media strategies if you’re a marketer.
4) Targeting. Knowing who the high-value shoppers are enables the organization to create highly tailored target audience groups, ideally those with a history of purchasing your product or products in your category.
5) Activating. Well-targeted campaigns ensure your company’s marketers reach the audience through direct linkages to publishers, programmatic buying platforms and media buying agencies.
6) Measuring. Very rapid and accurate campaign measurement can make or break a campaign. Rapid measurement allows teams to adjust media, pricing, promotion and other strategies while campaigns are in-flight, based on the level of shopper activation.
7) Optimizing. Adjusting campaigns while they are in flight, and leveraging measurement data to adjust products, layouts and campaigns rapidly captures shopper loyalty and revenues and enables teams to achieve optimal ROI.
If you are interested in learning more about personalization or expanding the big data capabilities within your company, please contact me at John.McIndoe@IRIworldwide.com.