Customer Data & Analytics Blog

AI, Marketing, & Big Box Retail: What You Need to Know

Katie DeMatteis | 5 minute read

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What's Happening in Big Box Retail?

Shoppers are demanding more from their shopping experiences, and big box retailers must be innovative or risk becoming obsolete. With the growth of online shopping, the factor which once set big box stores apart from their competitionconvenienceis no longer a differentiator.  eCommerce sellers offer a wider variety of products, with easier navigation than one would find in store.  Because of this, many large retail chains are downsizing, or closing completely.

Despite this movement, the United States is still vastly over-retailed.  From 1995 to 2015, the number of shopping centers in the U.S. grew by over 23% while our population grew less than 14%. This amounts to 50 sq ft of retail space per person in our country, twenty times as much (2.5 sq ft) as in Europe.  (The Robin Report)

This growth is simply not equivalent to demand, and it’s hurting retailers.  With the trend towards specialized stores, and mobile and online shopping, it is important for larger companies to listen to what consumers actually want:  Personalization.  Mass marketing doesn’t work the way it once did.  According to a PwC report, niche products, experiences, and services refined to individual tastes, interests, and aspirations have become “the new consumer indulgence.”

Personalize for Success

The best way to win over your customers, and keep them coming back, is to show them that you know them.  Many times, consumers feel like a faceless shopper in a warehouse of goods.  This makes them less likely to be loyal to one specific store, and more likely to change their purchase behavior.  The competitive advantage that companies like Amazon have is a personalized touch.  Consumers want the companies they purchase from to provide them with promotions and messages that are tailored to their specific tastes. 86% of customers say that personalization has an impact on what they buy/who they buy from and one third of customers feel that there isn’t enough personalization in their current shopping experience.

Big Data to Big Wins

The amount of customer information currently available is massive.  Browsing history, purchase data, social mentions, and spending trends are all sitting in data lakes and warehouses at your company waiting to be unlocked. When used fully, this data can show what customers are buying, when they’re buying it, and what they’re likely to buy next.  In this way, big data has the power to revolutionize how the retail industry interacts with its customers—by creating offers, and recommendations at the individual customer level, and through the channel they most want to engage with.

How AI Can Help

Although most large retailers already have tools and data scientists to help them make sense of their data, there’s an opportunity to implement an AI + Machine Learning based solution that can double or even triple the speed and accuracy with which they act on their shoppers data and preferences.

A popular way characterize data usage in retail is the three D’s paradigm: Data, Decision, and Pasted image at 2017_09_20 09_54 AM.pngDelivery. When collecting data, quality and completeness is paramount in order to give effective and reliable reports & predictions. Once a reliable metric has been established, analysis and decision making needs to take place. Trends in purchase history, for example, can be used to suggest relevant promotions or goods for specific customers that can be used to convert them into a frequent and higher value shopper.

The final D is delivery to the identified segments and cohorts through outreach and promotion. This stage requires a genuine approach, which is why human to human marketing outreach is still the most effective strategy.  Companies need to move through this cycle of data collection, decision making, and delivery quickly and accurately in order to resonate with their ever-changing customers.

To achieve this, there are two key things a business must do—and do well:

  1. De-silo, and unify your data.  In this way you can create a comprehensive and integrated view of your shoppers across all touch points, even enriching this data with third party information that goes beyond what they provide you themselves
  2. Leverage that clean and complete data to conduct deep analysis and draw correlations between thousands of data points.  This allows you to analyze and predict the behaviors that are most important to your business. Things like trend affinity, propensity to certain products (cross-sell potential), regional looks, promotions, and more

Here’s where an AI engine can help. Implementing Artificial Intelligence/Machine Learning enables the creation of systems that are both smart and adaptive enough to solve problems faster and better than a human ever could. This requires a Dynamic Data Engine (DDE) and an Embedded Analytics Engine (EAE).

To have a comprehensive view of your customers, you need to unify data across all of your sources: online, mobile, in store etc.  A DDE can identify, cleanse, unify, and enrich this data in real time, and for each individual customer.  Once this has been done, an EAE uses the curated data to predict customer behavior with minimal human intervention.  It can tell you, for example, that people who purchased a combination of seasonal decorations from your store in the winter are less likely to respond to general discounts, but more likely to respond to specific holiday promotions, and you can tailor your marketing accordingly.  It can also show you differences across demographics, and can suggest higher level ways to position your marketing across microsegments.

AI has the power and the speed to take care of the first two D’s (Data and Decisioning) quickly and well, with little human oversight after the initial training.  The power of these systems lies in their flexibility.  With the data you already possess, they can find the signals your customers are sending, and suggest the right time and way to create meaningful engagement. This frees up your time and energy to focus on “Delivery”.

ZyloTech for Big Box Retail

Big Box retailers have a huge opportunity here.  If your business can act faster, with more accuracy, and in line with customer needs, you will have a technological competitive advantage in your industryan advantage that could keep you relevant with 21st century consumers.

Using the ZyloTech platform, companies have leveraged years of data on millions of customers to drive revenue and increase retention.  Among other things, our users have seen 200% overachievement in retention, 4x increase in overall lift/LTV, and 35% reduction in customer churn.


Where Do I Go From Here?

If you’d like to learn more, or talk about a possible use case at your company, please get in touch with us so we can explore this together and see where you goals may align with an AI solution.

Topics: Personalization