Last updated on December 12th, 2024
By Mike Bristol/VP Personalized Marketing, Symphony RetailAI
Sometimes, the world seems to just turn too quickly; work projects kick into overdrive, kids’ schedules get too hectic, and even taking the time to pick out a somewhat healthy meal at the grocery store seems like a daunting task. As both consumers and busy, complex people, many of us crave simplicity and convenience when it comes to managing our day-to-day responsibilities. Fortunately, based on a Symphony RetailAI survey of 50 U.S. retailers, it’s apparent that most fast-moving consumer goods (FMCG) retailers today have the means to bring balance to our shopping lives by using personalized marketing, which makes it easy to find the items we want—or discover new items—exactly when and where we want them. However, the research also found that very few have actually executed a strategy to do so just yet.
Retailers understand that any lasting relationship with customers is built on trust—trust that items will be high-quality and fairly priced, in stock, supported by superior customer service, and more. But as consumers, we also trust that the retailer “gets us,” understanding our needs and preferences. With the rise of personalized marketing based on advanced customer intelligence, this last piece of the puzzle becomes even easier to achieve, but not without some foundational work from the retailer first.
Sourcing valuable customer data
Driving long-term customer loyalty and lifetime value down to the customer level takes a 360-degree view of each customer. The more precise the data, the more retailers can make marketing campaigns personal and precise to support bounce-back and new customer acquisition strategies.
Only five years ago, most actionable data came from POS systems, loyalty cards and outside data companies. Today, retailers can go further, bringing in unstructured product, sales, merchandising and supply chain data, as well as real-time data from in-store technologies like beacons, Wi-Fi and store video. Understanding how customers engage with a product, a store layout or options within a category—not just whether they buy an item—allows marketers to be much more precise with their offers and create desired outcomes that benefit all areas of the business. Taking it even further, today’s retailers can even incorporate third-party data from other retailers (including competitors), wholesalers and manufacturers, alongside historical industry data, to create an accurate view of each individual household.
While accumulating data from more sources provides a more complete data set, it also makes it exponentially more challenging to synthesize the data from disparate sources into an actionable behavior profile. In fact, while nine in 10 retailers target customers across multiple communication channels, many struggle to effectively leverage information gleaned on one channel to take effective action on another. For example, only:
- 60 percent target customers based on items browsed online
- 56 percent target customers based on precise locations
- 40 percent target customers based on purchase history
- 34 percent target customers in real time
Leveraging AI-enabled platforms and machine learning
This is where the rise of AI and machine learning becomes incredibly valuable for retailers and marketers. These systems can automate the development of unique shopper profiles and establish intelligent triggers for allocating relevant offers to those shoppers based on the data collected from each touchpoint. AI-enabled systems have the power to acknowledge, contextualize and react to every data point from all channels in real time, allowing marketers to focus on optimizing the content and offer set.
In large part due to the continued adoption of these technologies, and with 60 percent of respondents emphasizing marketing automation as their top personalized marketing capability, retailers expect to significantly strengthen their personalized omni-channel capabilities in the coming 24 months. By that time:
- 88 percent will be able to target customers based on items browsed online
- 88 percent will be able to target customers based on precise locations
- 68 percent will be able to target customers based on purchase history
- 82 percent will be able to target customers in real-time
Integrating personalization across channels
This growth in precise targeting will be vastly important in maximizing the impact of each marketing communication and will also reduce the generic marketing ‘noise’ consumers have learned to generally tune out. Yet as marketers become more adept at using our shopping behavior data to target us, they will need to become much more integrated across channels.
As it stands, 74 percent of retailers claim to have a high level of ability to carry out personalized digital marketing—social media, display ads, retargeting, etc.—in terms of reach; 60 percent claim a high ability to do personalized offline marketing. While that’s promising, a meager 16 percent claim a high ability to integrate personalized marketing across channels.
The future of retail will be more personal than it ever was, even when Sam, the local grocer, knew that your family always had steak dinner on Tuesdays and preferred chocolate ice cream. In the AI-enabled, truly personalized marketing environment we’re entering into now, Sam would know when to make an offer available to you, whether you preferred it to be sent digitally or printed on your receipt, and would be able to predict if you were thinking of checking out a competitor’s availability down the street. Today, these things are possible because of the vast number of data sources available and the power of technology to structure and simplify that information into highly actionable outputs.
The sun has set on the days of mass promotion. But when it rises for another busy day managing the important things in life, the fast-moving consumer goods retailers making strategic investments today will be there to help you find and buy the items you want, faster and more effortlessly than ever before.
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