TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Data: The Key to Helping Retailers Survive and Thrive

The pandemic forced many retailers and B2C companies to get online or fail. As we move into the post-pandemic landscape, how will these companies respond to the new reality?

• By Ohad Greensphan
• August 11, 2022

As we continue to move past COVID-19 and into a new post-pandemic era, brands need to pivot to stay ahead of competition and market changes. During the pandemic, it became clear that brands can’t really survive without having a digital footprint. When consumers couldn’t physically visit stores to purchase items, they turned to the only source available to get essential items (and many nonessentials). With the massive increase in the use of online platforms to purchase goods came higher demand for e-commerce solutions that would help brands continue to operate.

For Further Reading: Are You Ready for Algorithmic Retail? What Will Determine the Winners and Stragglers in the 2022 Digital Commerce Economy CMOs Must Partner with CIOs and CDOs to Enable Data-Activated Marketing

The “new normal” we have become accustomed to isn’t really the new normal. Even though, post-pandemic, the general population would prefer to buy in-store for certain products, retailers are wary of shifting focus back to brick-and-mortar operations because e-commerce helped many survive and that during this time, many thrived. As a compromise, companies are seeking ways to connect the digital world to their physical stores for the best of both worlds, and to create a profitable enterprise that serves consumers well. A significant part of getting there for many brands includes utilizing sophisticated data.

Navigating this new e-commerce reality -- both pure e-commerce and a digital/physical hybrid --is not easy, and B2C brands still face many challenges as they navigate this new post-pandemic market. The amount of traffic on websites grew exponentially over the past two years, creating more complex customer journeys. As more merchants entered the marketplace trying to sell their goods, competition also got fiercer -- B2C brands found it harder to stand out from the crowd and differentiate themselves.

Mid-market merchants and SMBs adopted new tools to help them take better advantage of these new, complex customer journeys but are struggling because there are many tools now available and it’s hard to know which ones will help the business the most. The connection between the digital and physical worlds is a difficult one too. For example, how do we know when someone has visited a store in person and, based on that knowledge, how do we target them for online purchases?

It should also be noted that even “post-COVID” there are still lingering pandemic impacts that will be felt by B2C brands for the foreseeable future. For example, we are still dealing with outbreaks and variants that sporadically send people back to their homes and out of stores. When this happens, the number of visitors to websites rises, but this is a positive situation only to a certain point.

Given recent changes in privacy regulations, online merchants need to use non-personally identifiable information (non-PII) to help reinvent themselves. This data needs to go beyond basic demographics and dig deep into shoppers’ purchasing intent and how to better craft their journeys based on non-PII data points.

Non-PII data offers brands a new way to deepen personalization without compromising shoppers’ trust and privacy. It’s anonymous data that can’t be used on its own to identify a person but rather identify if that shopper is on a slow web browser, what type of device they’re shopping from, and the weather in their city/region, among other details.

Increasingly, brands can use in-depth data based on artificial intelligence (AI) and machine learning (ML) to gather information about what shoppers are doing on the website, where they are clicking, where they are dropping off, and more. AI and ML platforms can predict shoppers' intent by learning from each visitor’s unique signals and digital behavior in real time, and then delivering the optimum promotion (e.g., prices not too high and not too low) -- or no promotion at all -- to each session to ensure that shoppers complete their journey.

For instance, this data could discover a correlation between shoppers with low CPU power and high checkout abandonment, indicating that the brand should disable video for those shoppers, improving their experience and decreasing checkout abandonment.

With this non-PII data, marketing strategy can become more coherent and consistent, leveraging information unique to the industry and truly relevant without invading shoppers’ privacy. Businesses want data that is actionable and can make a difference in the way they communicate with shoppers while staying within privacy regulations.

As we move beyond COVID-19 and into a possible recession, technology and data can help usher in a new channel of profitability for businesses of all types and industries by identifying on-site personalization based on customers’ behaviors and intent.