2022: The Year Ecommerce and In-Store Become Intertwined

If 2020 was the year of lockdowns and e-commerce growth, and 2021 the year of a nostalgic return to stores, 2022 is the year we’ll see the two channels become closely intertwined. Savvy consumer goods companies and retailers need to understand the relationship between their physical presence and online sales. Key to this is tapping into advanced analytics that can help them both identify correlations and signpost optimal business decisions to drive sales in both. We expect ecommerce to continue growing in 2022, reclaiming the momentum it lost last year when in-store sales surged and, at certain periods, outpaced ecommerce. But, despite this return to the online sales boom of 2020, the continued importance of traditional in-store distribution should not be underestimated. Many of our customers have detected strong correlation between physical footprint and online sales from the same area. The logic behind this relationship is simple: a strong physical presence in a specific location through on-shelf visibility and neighborhood marketing campaigns helps strengthen brand awareness, which in turn contributes to online sales. This is especially true for newer or niche brands.

What we saw during the last 24 months

2020: The first year of the pandemic saw shoppers flock online. Quarantine-led indoor activities drove up sales in everything from puzzles and home exercise equipment to baking, decorating, and homeware. One of the biggest pandemic trends was amateur baking, spurring the banana bread and sourdough baking phenomenons of spring 2020. Noogata saw searches for sourdough bread spike in spring 2020, with the search frequency rank for “sourdough bread” moving from position 91,356 in March 2019, to position 1,972 the month of the pandemic. 2021: In-store sales rebounded with above-average growth in return-to-office categories like apparel and jewelry purchases, as people prepared for the end of remote working. The holiday shopping period began much earlier than usual, driven by early Black Friday and Cyber Monday promotions, and customer concerns around supply chain interruptions and product shortages. In 2021 “Christmas decorations” was the #1 ranked search term on Amazon as early as the week starting October 31. In 2020, the term did not reach the #1 ranking till the week of November 29.

Amazon Rank for ‘Christmas Decorations’ Search Term

Data transforming business challenges

Data is more important than ever before. In 2020, the emphasis was on identifying growth products and optimizing product content to maximize search traffic. In 2021, this shifted to thinking more about physical distribution, identifying and scoring leads and analyzing omnichannel data to identify which locations offered the most promising growth opportunities. In 2022 and beyond, consumer goods companies and retailers need to ensure their spending on technology and data focuses squarely on solving their most pressing business challenges. Are they lagging in ecommerce? Then they need to maximize organic search exposure by optimizing product content. Are they looking to expand in-store distribution of their products? They’ll need to identify the best regional opportunities for growth and be more targeted in their sales and marketing campaigns. And, most importantly, they need to look at their data holistically, through a lens that focuses on spotting correlations between ecommerce and bricks and mortar activity, and learning which levers have the most impact on overall sales. Beyond these use cases, companies need to make an intellectual shift in which they are deliberate about linking data strategy with clear business outcomes. Organizations often claim to have a “big data strategy.” Too often however, companies want to know as much as they can about their customers, markets and competitors and collect huge volumes of data accordingly.  But without a clear business purpose for collecting this data, it can become a liability. They must first define the questions and business challenges they want to address, and then go about collecting the data needed to answer those questions. Having a technology platform that enables companies to answer a range of business questions is critical today. Artificial Intelligence (AI) certainly offers the means to process and derive valuable insights from data. But to fully tap into that potential, AI needs to be in the hands of the people who need the insights and who make the decisions. For this to be possible it is important to simplify the way that AI models are developed, trained, and deployed. This is where Noogata comes in. Our AI models have all been built to solve specific business challenges, which radically reduces the time needed to see results and deliver ROI. Additionally, the Noogata platform is open and flexible, providing users with the tools they need to integrate and enrich relevant data, fine-tune models and compose workflows in a way that is most useful for their business, but not locking them into our workspace.