How accelerated digital transformation has changed (physical) retail

Eduardo Borrotchin
How accelerated digital transformation has changed (physical) retail');

The retail and eCommerce landscape is rich, diverse, and constantly evolving, fueled by a continuous supply of digital optimization tools in a challenging digital transformation environment.

In 2019, a total value of $3.4trillion sales was carried out in the global online marketplace and by this year, online retail sales are set to reach $4.8 trillion. According to Business Insider, in the US alone eCommerce represents almost 10% of retail sales — a figure that is growing by nearly 15% each year.

Despite the steady rise in eCommerce adoption, 86% of total retail sales is still taking place in physical stores. Yet, most consumers’ online identities remain disconnected. According to the latest report from Westfield, 56% of shoppers are frustrated by inconsistent and inaccurate online recommendations. 74% of shoppers will try a new brand on impulse in-store and they’re more than twice as likely to impulse shop in-store then online.

As retailers navigate towards an “accelerated” digital transformation in the post-COVID era,  in-store purchasing is still a massive chunk of a retailer’s business. Therefore, the right strategies should be put into place to provide a relevant, accurate, and personalized customer experience.

The journey from physical store to omnichannel approach is key to address the main assets of the business and ensure valuable data is not going to waste. Here are some key insights into physical retailers that will make you think about what is possible and what consumers want in this ever-changing world of retail.


1. The rise in “AI for Marketing” 

Marketers in retail are facing a highly complex task. On the one hand, a massive growth of digital touchpoints that has resulted in an increasingly difficult job of collecting data and getting customer intelligence and predictions out of it. On the other hand, consumers have very high expectations when it comes to brand interactions, content, and personalization.

The rise in popularity of AI techniques for marketing has provided retailers with new customer targeting opportunities. Combining real-time customer purchasing data with the adoption of machine learning modelswill enable marketers to use their in-store data sources (where some the most valuable data is available) to create smart predictions and define a proper personalization strategy.

Many large retailers have using this to great effect in the past few years, but they should invest more in personalization strategies and contextual programmatic advertising in-house to create relevant and accurate targeted audiences. This will result in campaigns that deliver higher conversions and revenues.

2. From physical store to an omnichannel model

The evolution from brick-and-mortar into the new omnichannel reality of eCommerce was driven by consumer demand. The challenge remains in how to achieve the real-time and seamless integration between multiple online and offline channels – and move away from ineffective marketing campaigns that do not connect with customers.

But even more challenging for most retail marketers is budget dilution across the different digital channels, without proper offline (in-store) ROAS measurement. In order to calculate retailer’s omnichannel ROAS, one should use this formula: (Online Revenue + In-Store Revenue) / Campaign cost.

In order to include the physical retailer in the omnichannel ecosystem, marketers carefully need to consider building a unified customer profile across all touchpoints (offline and online). Attributing every marketing dollar to online revenue, while overlooking in-store sales, will result in inaccurate reporting and uninformed ad spend.

Retailers should consider taking the following steps:

  1. Connect in-store consumer purchase behavior to the customer’s online identity
  2. Create a unified customer profile
  3. Invest in segmentation and data enrichment to enable for smart predictions
  4. Define personalized audiences that are accurate and relevant
  5. Predict & recommend personalized campaigns
  6. Measure a Omnichannel ROAS

3. Understand your customers

There’s a common theme with all of the points above: data. We live in the information age and, as a consequence, we have access to more data than ever before. Marketers have access to historical business data, transactional purchase behavior, and social feeds that allow retailers to bring together a rich understanding of their customers: What they are doing? How are they doing it? What and where are they buying?

As technology evolves, the line between the offline and online world is getting blurrier and smaller. In the post-COVID era, customers will spend a lot of time in physical stores again, and retailers need to understand how to make customers feel unique and relevant.

In an ideal world, this should be replicated in the online world. As a retailer with digital ambitions, the goal is to connect offline and online worlds and create a unified omnichannel experience.

This focus on customer-centricity provides consumers with a connected, consistent, an relevant experience across channels. Knowing more about your customers allows you to tailor your marketing to each individual user, moving away from mass campaigns with little known data. These insights, if properly used, should enable decision makers to make smart predictions based on actionble data to drive change and influence positive outcomes when engaging with customers across all touchpoints.


Despite such rapid growth in the online retail sector, 46% of consumers still prefer the brick-and-mortar experience over online shopping. This is even more relevant for products of high value, such as jewelry, clothing, and cosmetics.

Retailers, therefore, need a customer-centric approach to the offline and online experience, which entails accurately recognizing a consumer across all their touchpoints (including physical stores) and tying those back to central unified profiles. This practice ensures that all messaging is informed by a rich, historical, and ongoing understanding of the individual, allowing for one-to-one communication.

By investing in AI marketing tools, retailers will be able to leverage the powerful techniques of data science and machine learning inputs. The result: unlimited opportunities to engage consumers. With AI at the helm, retailers will no longer have to promote their offerings over every single platform. AI inputs will gauge the customer search patters and only display the relevant communications to individuals searching for the same, creating a personalization.

Last but not least, retailers will be able to target the most relevant audience with the right offer at the right time, without continuously delivering communications that fail to connect with a consumer.



Author Bio
Eduardo Borrotchin is SVP at Pairzon AI, a leading AI technology solution for retailers that is driving disruption in the bricks-and-mortar market. They connecting in-store consumer purchase behavior to online costumer identity, bridging the journey from in-store to omnichannel and enabling retailers to boost sales, retention, and customer engagement.

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