Despite the tumultuous year, ecommerce expectations are high this holiday season.
The massive shift to online shopping brought on by the global pandemic fueled predictions of a greater than 40% increase in year-over-year U.S. holiday ecommerce sales. A delayed Amazon Prime Day performed well as a holiday teaser. Its success signaled a strong appetite for online shopping and an opportunity for brands to capitalize on the highly lucrative annual Black Friday/Cyber Monday (which have evolved from the single-day sales of years past).
While the ecommerce skies look bright, brands and retailers can’t sit passively and wait for the marketplace to serve their share of the holiday pie on a silver platter. Customers have a dizzying amount of choice with an ever-widening moat of competing brands and new entrants—from Amazon’s array of branded products to countless direct-to-consumer brands that fill shoppers’ social media feed, email inbox, and TV screens.
The more things change, the more they stay the same
While so much has abruptly changed this year in retail and ecommerce, the recipe for success remains constant. Retailers need to understand who and where their existing/potential customers are and then provide a memorable brand experience. Price is and always will be a factor. Still, superior experiences can win the day, especially in highly contested holiday verticals like beauty and cosmetics, consumer electronics and fashion and apparel.
Data is a powerful source of insights for discovering, targeting, and converting customers in the online world. Here are three data strategies that brands and retailers should check off their readiness list as the holiday shopping clock winds down and competition for customer mindshare—and money—heats up.
1. Review your data and apply it appropriately
Data is essential for holiday ecommerce and marketing/advertising success. It empowers brands and retailers to make fact-based decisions about marketing/advertising, merchandising, product pricing, and more. However, retailers often face a common problem: too much data, too little time. Data is essential, but it isn’t a monolithic silver bullet for every problem. Audit your different data types and sources now to make sure something important doesn’t end up wasted like a stale fruitcake. Here’s a quick breakdown of common data types along with relevant use cases.
- First-party data that you collect from your own sources, such as customer past-purchase and demographic data, is good for promoting everyday commodity items and fueling holiday reward/loyalty programs and campaigns.
- Second-party data that you may have purchased from other organizations is useful for vertical-specific targeting and reaching new audiences. For example, you’ve launched a completely new product line for the holidays and need to find people interested in those products.
- Cookie data is useful for creating look-alike models (building larger audiences from smaller segments) and remarketing. For example, you want to expand and optimize your list for a targeted multi-channel programmatic campaign that includes special holiday messaging. There’s been lots of buzz about the future of advertising ever since Google announced its plans to end support for third-party tracking cookies within two years.
- Social media data is useful for uncovering future-purchase intent, understanding customers across categories and creating brand-level act-alike models. Social is a strong and reliable channel to learn about shared interests amongst consumers and active engagement (what gifts and brands that consumers are talking about online in real-time) can signal actual purchase interest.
2. Leverage data within a broader conquest strategy
Once you have a handle on what kind of data you have and how to apply it, you can then map out a conquest strategy to take advantage of brand and category-specific consumer queries that are happening online in the absence of in-person shopping. Because that in-store organic discovery that occurs with customers browsing physical shelves is missing with the shift to online, retailers must intercept shoppers digitally in very targeted ways. Something to look at closely this holiday season is programmatic and addressable TV. Studies show that TV is still the best video platform for advertisers seeking to grow market share.
Data strategy is essential here. For example, if you want to cast a wider net to capture new addressable audiences in a way that mimics the way consumers browse physical store shelves, modeling data can help. Modeling with social data for addressable TV can help move past broad, category level targeting. Social data can reveal fans at an individual level, not a household level, and provide better insight into who is watching and who is most likely to watch, which boosts return on ad spend.
3. Examine and utilize gifting-specific data
The very nature of the holiday shopping season presents challenges for brands and retailers regarding data. Yes, people take advantage of the season, including Black Friday/Cyber Monday sales, to shop for themselves. Still, when shopping for others, many traditional uses of data are rendered less useful. For gift predictions and recommendations, data can come from explicit queries (e.g., ask the online gift shopper questions like who they are shopping for and what the recipient likes and their desired price range). However, this often leads to generic look-alike recommendations based on demographics.
In 2016, HUGE had a great article about the challenges with balancing automated and manually curated gift recommendations. Four years later, actionable data for gift-giving is still a challenge, though some progress has been made in certain areas. Companies like Smartgift enable actionable insights based on recipients’ actual product preferences, post-receipt social engagement, purchase occasions, and customer relationships for year-round, data-tailored marketing initiatives.
Wrapping things up
It will be a while before consumers are comfortable flocking to malls and physical stores en masse. Now is a good time for retailers to focus on their ecommerce and digital strategies—and this requires a robust and scalable data strategy. While more online shoppers create more opportunities, it also means increased competition.
An effective data strategy includes reviewing and applying data correctly, improving audience targeting across key channels, and exploring new, gifting-specific data sources. With this approach, brands and marketers can effectively reach likely buyers during this and future holiday seasons.
Affinity Answers is a data analytics company. It analyzes data collected by capturing the positive, pseudonymized engagements (both likes and comments) between people on social media and the content posted by more than 70,000 brands, TV shows, movies and other media and entertainment properties.Favorite