The new pandemic consumer: 7 insights on your new 2020 customers

Let’s take a short trip back to March 2020—no mask required.

Consumers were facing a global pandemic, and suddenly, all of their shopping habits were turned upside down.

Brick-and-mortar stores were seen as hazardous, and those that ventured out faced empty shelves. Eighty five percent of consumers across generations said they couldn’t always find the items they were looking for. Many people filled their carts with panic buys, the most popular of which were paper products, fresh produce, and canned and dry goods.

Consumers that didn’t want to shop in-store were instead shopping heavily with Amazon, mass merchandizers, gardening and outdoor stores, as well as Costco.

And beyond the logistics of shopping, life for most looked totally different than pre-pandemic days:

• People spent inordinate amounts of time in their homes.
• Working from the kitchen table.
• Amusing and/or teaching children seven days a week.
• Preparing more meals for themselves and their families.
• And filling free time they were unfamiliar with.
• Many people bought new products to help them adapt to these new circumstances.

Forced to shop for new needs, with new retailers, for new brands, via new channels, it’s no surprise that many brands had new customers during the early days of COVID-19.

This raises a lot of questions:

• What are brands to do with these new customers?
• How likely is it that the brand can keep these new customers long term?
• Do these customers differ from their regular customer base? And if so, how?
• Do they need to talk to these new customers differently? How?

To answer these questions, we analyzed Epsilon’s Abacus Cooperative database to glean transaction-based insights across 525 retailers, both in-store and through online, call center and catalog channels. Our goal was to understand what new customers popped up for brands during the pandemic, how they differed from those brands’ past customers, and if those customers remained loyal to the brands over time.

Our data showed consumer behavior, habits and preferences have, in fact, evolved—indicating relevant, purposeful shifts that brands need to account for moving forward. The full report, The Variable Pandemic Consumer, can be accessed through the slideshare below, and we’ve compiled the most interesting insights with a little more context to dig into here.

Table of contents: 

• Key Insights—Early Pandemic 
• Key Insights—Later Pandemic 
• Key Insights—Leaving 2020 Behind
• What should you do with this information? [Recommendations]

Key Insights—Early Pandemic 

Brands had many new buyers through direct channels.

Brands saw a 43% increase in new buyers across direct channels in 2020 compared to the previous year—and many brands didn’t even have to work for it. Marketing was a distant concern when these brands couldn’t keep products on the shelves. Others had plenty of merchandise but weren’t able to physically retrieve it from their warehouses due to lockdowns.

Repeat buyers were also up on direct channels with a 17% increase in year-over-year repeat buyers.

Unsurprisingly, brick-and-mortar retailers have struggled during the pandemic. In-store buying was down significantly between 2019 and 2020—brands saw a 73% decrease in new buyers through brick-and-mortar channels.

New buyers were younger and more diverse

The new buyers brands acquired in 2020 were a younger, more diverse group compared to the same year’s repeat buyers. They had lower incomes, less education, were less likely to be married, less likely to own a home, and many were just getting settled into new homes.

This segment of new buyers was not all about panic buying. They may have also been more likely to shop new brands because they were less established at the start of the pandemic—and therefore needed items to set up home offices, amuse and educate children, cook more meals, take up new hobbies to fill time, etc.

Conversely, the repeat buyers demographic skewed older, with more income, they were more likely to own a home, and they were more likely to have been in their home for over two years. They probably shopped fewer new brands because they just didn’t need as many new items to weather the lockdowns.

This group of new buyers was also likely driven to try new brands—even when they weren’t new to the category—to deal with stock-outs. Take sweatpants and other leisure wear, for example. Many brands sold out during the early days of the pandemic, so buyers may have looked to new retailers to stock up on comfortable attire.

New buyers visited less—but spent more

Spend: In 2020, new buyers spent more per order than repeat buyers across channels.

• New direct buyers spent $142 per order, whereas repeat direct buyers spent $134.
• The difference between in-store buyers was more stark—new buyers in store spent $277 per purchase compared to repeat buyers’ $110.
• That said, repeat buyers still made up the bulk of direct purchase activity.

Frequency: While new buyers spent more per order in 2020 than repeat buyers, the repeat buyers shopped more often.

• In direct channels, repeat buyers transacted 2.7 times per household compared to 1.6 for new buyers.
• The trend was the same for in-store purchases.
• Repeat buyers had 2.6 visits on average, whereas new buyers only had 1.8 visits on average, and both were mostly in line with 2019 patterns.

Key Insights—Later Pandemic

Brands retained more new buyers from direct channels

After experiencing the convenience of online (and other forms of direct) shopping, it appears that some people were happy to continue with it.

In direct channels, brands retained 39% of the 2020 new buyers that shopped March to May—an increase of 6% year over year. This is a stark contrast to the cohort of new in-store buyers, which brands retained at 34%—an 11% decrease.

At the end of the day, 78% of all direct buyers (new and repeat) between March and May re-bought with the brand between June and December. In-store buyer retention wasn’t far behind. From June to December, 73% of the March through May buyers were retained. Overall retention was flat year over year. And important to note that lockdowns and stay-at-home orders varied greatly by geographic area during both periods. Some areas were practically fully open while others were still being very cautious.

Repeat buyers were anxious to get back in store

As 2020 wore on and lockdowns were eased in some areas, buyers were anxious to get back in store.

Both spend per household and transactions per household in brick-and-mortar stores were up year over year from June to December. This holds true across both new and repeat buyers. Repeat buyers were especially busy with shopping trips in the latter half of the year, averaging 10.7 in-store transactions per household (compared to only 6.8 in 2019 and only 6.0 for new buyers in the same time period).

Spend and transactions in direct channels between June and December 2020 saw more modest increases over the same period in 2019. Repeat buyers were still shopping more compared to new buyers (6.2 vs. 4.1) and spending significantly more per household ($840 vs. $560).

Consumers made fewer but bigger purchases online

Despite all of their in-store shopping in the latter half of 2020, both new and repeat buyers spent less on each of these in-store transactions compared to their direct purchases. Both segments made less frequent but higher value purchases in online and other direct channels.

In-store AOV spiked—then flattened

The 2020 average order value for new buyers in store was significantly higher in the March to May timeframe, indicating early panic buys, as well as preparing the household with items needed for lockdowns.

But this in-store spending trended back downward as the year wore on, landing at $64 per order (a 26% decrease from the same period in 2019). The lower AOV in late 2020 could be related to the significant increase in transactions per household.

Despite a smaller increase in new buyer spend at the start of the pandemic, the AOV for direct was relatively flat from early in the crisis to later. The average order in direct channels was about $135 across the year and across new and repeat buyers. Interestingly, average order value in direct channels was up significantly year over year for 2020, across new and repeat buyers.

It’s worth noting that the AOV for direct channels is significantly and consistently higher than in-store AOV. Brick-and-mortar stores need to focus more on moving inventory than their direct counterparts and therefore rely on clearance pricing, reducing order value. On the flip side, shipping fees drive up AOV for direct channels as buyers load their carts to reach free shipping thresholds.

Key Insights—Leaving 2020 behind

Now, it’s important to explore what’s happening to all the new buyers that we met in 2020. How did they fare into 2021 compared to their counterparts from 2019? We found that new buyers from 2020-2021 had a higher AOV and more transactions per household than their 2019-2020 counterparts (if you'd like to see 2019/2020 comparison numbers, check out the full research deck at the beginning of the post). 

Retail buyers during March – May 2020 are repeating at a higher rate in in-store shopping than the year before, but still lower than Direct. Repeat buyers had a much higher retention rate and number of transactions per household YOY, though their AOV was significantly less, suggesting people made more trips for fewer things or at lower price points.

So what do you do with this information? [RECOMMENDATIONS]

So now that you have this information, what do you actually do with it?

Leverage transactional data to better understand who’s buying—and who’s not

• Transaction data is always the best source of truth when it comes to customer knowledge. Through the lens of new versus repeat buyers throughout 2020, this data can tell you which of your customers are still buying in your category, who is new, and who has dropped off​.
• First-party data is the best way to understand your current customers, but it’s important so supplement with third-party data that can help to provide the whole view of what brands your customers’ engage with. Epsilon can help fill that data gap for many brands and help them connect disparate data sets into one cohesive view of the customer across channels. For example, your data may show that someone is a heavy women’s retail buyer, but Epsilon data shows they’re buying kids clothing and accessories elsewhere. That’s an opportunity to get them to purchase all categories with your brand.
  • See how we helped Kimberly Clark align their first-party data

Identify areas to simplify the online/direct buying cycle​

• The research data confirms increases in quantity and AOV of direct transactions. While this may feel seemingly obvious that more people are buying online due to the pandemic, it also presents a greater shift in buying habits for consumers—they’re buying things online that they used to only buy in-store (since they’re buying everything online). Many are finding that they prefer to shop for certain things online over in-store or they prefer the convenience of online order for pickup.
• Brands need to make that transition seamless in all cases. Walgreens does a great job connecting the consumer experience through its loyalty program (which Epsilon powers), offering a personalized experience for each member on its app that then translates into 1:1 reminders and offers when they’re shopping online or in-store as well.

Invest in your data and continuously monitor it ​

• This won’t be the last disruption so it’s important to not only bedata rich but also insights driven—evolving as the customer does over time to accommodate new habits, and preferences. Keep in mind that every purchase from a customer is not a “one and done” but instead a continuous learning loop. There is always more insight to be gained as relationships build over time.
• 2020 was an unprecedented year—but as the pandemic continues, there is more to learn from 2020 that will inform this year’s strategy and into next year. Using data to understand and identify anomalies versus real opportunities with consumers is critical for your marketing strategy to succeed.

 Methodology

For this project, we used Epsilon’s Abacus Cooperative database to identify and profile customer segments by purchase channel. Our research included data from 80 brick-and-mortar retailers (in-store) and 445 retail brands with an online and/or call center and/or catalog presence (direct).

Did you know? Epsilon’s Abacus Cooperative database is the largest cooperative database in the U.S., in which more than 3,000 contributing brands across B2C and B2B categories pool their transactional data. 

In-store segments

• New Buyers: Brand new in-store buyers across the 80 retailers from March 1, 2020 through May 31, 2020. These households had not purchased with the brand providing data in at least the last five years.
• Repeat Buyers: Existing in-store buyers who purchased from March 1, 2020 through May 31, 2020 and in the last five years with one or more of the 80 retailers.

Direct segments

• New Buyers: Brand new buyers across the 445 brands with direct channels from March 1, 2020 through May 31, 2020. These buyers haven’t had a direct-based purchase with the brand providing data in at least the last five years.
• Repeat Buyers: Existing direct buyers who purchased in a direct channel from March 1, 2020 through May 31, 2020 and in the last five years with one or more of the 445 direct brands.

For comparison purposes, these same segments were identified for 2019 using historical transactions with the same in-store and direct brands (referred to as 2019). The 2020 segments are referred to as 2020. Spend rates and metrics for each of the four segments were assessed for March through May and June through December in 2019 for the 2019 buyers and in 2020 for the 2020 buyers.

Note: This research contains aggregate transaction data for the entire United States. Regional results and experiences may have been different due to local closures and non-closures.