Cincinnati based American retailing company, Kroger, functioning since 2007 adopted a data-driven retail marketing technique to evaluate and escalate its operations. The goal of its project was to decrease out-of-stock items, augment revenues, and enhance customer experiences.
Kroger’s approach of customer segmentation in retail via data analytics has been particularly impressive. At the culmination of the project, the retailing company witnessed a reduction in their inventory by $120 million, an $80 million increase in revenue, and a reduction in their number of out-of-stock prescriptions by 1.6 million.
This is just one example among the multitudes that firmly testify the indispensable role of data and analytics in generating the desired ROI for retailers. Trust me, in this digital age, sans data, you’ll be lost. And if you look at all the successful retail marketing models, it is data analytics that plays the key role up there to achieve better consumer engagement.
So, I’m not surprised that most retailers are thus turning towards data-driven retail marketing these days. After all, we need results for every bit of marketing, right?
Now you don’t be capped. I’ll show you the ropes of customer segmentation and data-driven retail marketing to give you a leg up among your competition.
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10 Data-Driven Campaigns Every New Age Retailer Should Do
The idea here is to develop distinct segments of your clientele base. Creating these deep profiling cheat sheets for each of your buyer personas will help you increase your engagement metrics by tailoring your marketing efforts.
For instance, though your consumers cater to footfalls and purchases, you might not have a high ATV. So, what you can do here is, understand the particular customer segment thoroughly. Probe the kind of products they buy, explore their demographic attributes, and e-commerce browsing preferences. Use these insights to draw a conclusive, and collective persona for all your campaign planning and execution efforts.
Your role isn’t over with the customer segmentation for the behaviour of your clientele base would keep fluctuating with the changing trends. This means that personas from one segment can move into another segment too. A case in point is a VIP customer moving into a lapsing customer for inactive business transactions.
And as a business, you need to capture these movements in the nub, propel the upward movement and curb the downward movement of customers to be able to run successful marketing campaigns.
As a retailer, you could have numerous brands and departments with various offerings for your customers. In order to predict their ‘likelihood to purchase’ you need the help of advanced analytics models. These models would offer an accurate result by analyzing the historic data of millions of customers.
Let’s say that you want to run a campaign for a particular brand. With retail predictive analytics, you can curate your target audience for a particular campaign. This earns better results than simple heuristic based campaigns.
This is an interesting metric for observation, wherein you monitor the inter purchase time of different customers from various outlets to trigger the campaigns accordingly. For example, imagine that you are a retailer selling shoes and that you are aware of the inter purchase time of repeat purchase. Let’s say it stands between twelve to eighteen months. Then, based on this data, you could reach out to all your customers whose last purchase was twelve to eighteen months ago via triggered campaigns.
This campaign is quite common across various industries, right from hospitality to aviation. Fundamentally, your recommender systems must be able to give you product recommendations at individual consumer levels, taking all transactions into consideration over a timeframe.
You would have seen this in e-commerce sites. Once you check out or add items to cart, you’d get custom product recommendations. This applies to the retail industry too. If done right, you’d see substantial results. In fact, a lot of my clients have achieved a conversion increase rate of about 10% through our targeted product recommendation campaigns.
Oftentimes, you’d see one group of customers acting favourably towards your business. Say they could frequently purchase a specific product of high internal margins. Form the business forefront, identifying these consumers would be a savvy move. Then, with that data as your base, you can identify other prospective customers with similar demographic attributes. These “look-alike” customers should be stimulated to make a purchase through targeted marketing.
This is an extension of our consumer segmentation campaign. Here, you’d be able to detect the group of consumers whose buying frequency is high but with a low ATV. You can reach this group with coupons that incentivize them to buy a little more than their usual ATV in place of the discount.
To illustrate, consider a frequentist segment with an ATV of $50. You could give them a conditional coupon offering a 10% discount on purchases above $60. This tactic would help you increase the ATV from $50 to $54, and the same can be encouraged in the future.
With advanced analytics, you can predict the likelihood of a purchase by a particular customer in the next n units of time. You have specific algorithms that aid in this prediction. As a retailer, you should leverage these models to run campaigns simultaneously.
Trigger campaigns work perfectly for both online and offline retail. Think of the times you’ve received emails triggering you to check out an abandoned cart. Now, that's a classic example of our discussion here. So, customer actions such as add to cart or time spent on a page, etc., can be captured as events or triggers to be launched as campaigns.
Being in the retail space, it’s imperative for you to reach out to all your prospective customers and acquire them. Most important amongst this target group are those who have already demonstrated interest in your products and services.
You could show highly targeted ads on social channels to prospects who have recently visited your website. This is a simple demonstration of a remarketing campaign and could be used in all social channels.
Take it to Practice
To be successful, you need to reach out to the right segment of your customers, with the right product, at the right time, through the right channel, with the right offer. This is the name of the game. Use my retail marketing tips to augment sales and customer satisfaction. As you see, data-driven retail marketing campaigns are the wands that decree success. Be sure to take it into practice and see how it transforms your marketing efforts.