Shopper Insights

How Sweet Will Valentine’s Day Be for Retail?

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Last year, Valentine’s Day spending hit an all-time high. While this year’s projection is a bit lower, $18.2 billion is still nothing to scoff at. Here are some other highlights from an annual survey by the National Retail Federation and Prosper Insights and Analytics:

The average spend is projected to be $136.57, down from $146.84 last year.

The top three categories of spending according to projected dollars spent:

  • Jewelry ($4.3 billion)
  • An evening out ($3.8 billion)
  • Flowers ($2 billion)

The top five categories by percentage of shoppers planning to purchase within that category:

  • Candy (49.7%)
  • Greeting cards (46.9%)
  • An evening out (36.6%)
  • Flowers (34.7%)
  • Jewelry (18.7%)

Locations where Valentine’s Day sales will occur:

  • Department stores (35%)
  • Discount stores (32%)
  • Online (27%)
  • Specialty stores (18%)
  • Florists (18%)
  • Local small businesses (15%)

Valentine’s Day is obviously a popular gift-giving holiday, and while consumers may be looking to save more this year, there are still plenty of opportunities for retailers to deliver compelling promotions that drive purchase behavior.

Although the most popular categories for Valentine’s purchases may not be relevant to all retailers, President’s Day is also on the horizon. Often somewhat overlooked as a major shopping occasion, it is one of the first federal holidays of the year, with retailers offering a variety of deals (typically heaviest across the categories of home goods, appliances, mattresses, and apparel).

How to Better Plan for the Holidays

With two holidays to plan for in February, it’s important to analyze historical data to help better predict and plan for the coming season. Here are a few competitive analyses we recommend running to ensure optimal decision making, no matter which holiday is coming up:

Promotional mentions: Compare how other retailers are running promotions across your key product categories. Get insight into promotional frequency over time, promotional mix, and cadence. You can then use these insights to spot trends and gauge competitive threats to become more proactive.

Here you can see that both Zales and Kay had a spike in promotions in February of last year, but the peak promotional count occurred earlier for Zales. If Zales is a key competitor for Kay in a given category, they might consider adjusting their promotional calendar the following year.

You can also compare how the number of promotions and the distribution of promotion types changed from week to week across a set of merchants during a similar time last year. That provides insight into what types of promotions your competitors may be planning on running this year.

Product assortment distribution: Optimize your product assortment to meet customer demands by proactively identifying opportunities where there are assortment or category gaps. You can also identify demand patterns over time for better forecasting.

For example, you can see that both retailers’ women’s jewelry assortments are heavily skewed towards rings, but while necklaces are second for both, Kay has a much larger assortment compared to Zales (in terms of both percentage and SKU count). If they are looking to expand their categories, this could potentially be a good place to start.

You can also analyze assortment as it relates to pricing to get a sense of relative pricing, assortment distribution by price, and other competitive pricing trends. For example, if a luxury retailer sees that its pricing may actually be on the lower side within a key category, it may want to reevaluate its strategy.

These are just a handful of the insights that Wiser provides to help retailers and brands make better decisions.

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Better decisions can only come from better data.

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