Invoice-based data and depletions reports have obvious utility to beverage alcohol suppliers aiming to track the speed and volume of products moving through the three-tier system in the United States, but there is a lot that they can’t do, especially if you are trying to understand the behaviors of the end consumer. There are a few reasons why this is.
First off, depletion data is typically looked at by the standard 9-liter case for wines and spirits. For those who don’t know, this standardized case volume allows for the direct comparison of sales volumes for products sold at different sizes, i.e. 6 1.5L bottles, 9 1L bottles and 12 750ml bottles. This equivalized volume is important to normalize the data across different package sizes, but there is a major drawback: this measurement only tracks what products enter the retailer’s back door off of the distributors’ truck, not what products leave the store in customers’ baskets.Depletion data only tracks what products enter the retailer’s back door, not what combinations of products leave the store in customers' baskets, which is what we really want to know. Click To Tweet
Depletion data, besides being measured in the standard 9-liter case, is typically measured by % change between different time periods, such as year-over-year, in both dollar sales and unit sales. This information is important to suppliers so they can understand how much product they are moving and how much revenue they are generating, compared to a previous range. On a high-level, this can indicate relative performance of brands, products and categories, but there is a lot more to the story.
To put it simply, compared to consumer-focused analytics provided via retailer POS scan data, depletion data isn’t enough because it only measures how much product is moving through each tier, not how products are moving out of retailers’ doors in the hands of customers.
Analysis of data gathered about each individual transaction from a retailers’ POS system, including how products move out of retailers’ doors in customers’ shopping baskets, what products are bought together and what date/time they are purchased, can be used to measure customer shopping behavior and individual product trends.
Shifting your focus to customer-centric metrics allows you to analyze different factors that can influence sales and begin to understand the decisions made by customers standing in front of the shelf. Forcing yourself to reconsider your analytics perspective isn’t necessarily easy, but once you understand why customer-focused metrics can be so much more powerful than the depletion data the industry has relied on for decades, it will all be worth it.Shifting your focus to customer-centric metrics allows you to analyze different factors that can influence sales and begin to understand the decisions made by customers standing in front of the shelf. Click To Tweet
Here are two ways to increase off-premise sales by leveraging consumer-focused analytics.
Using Basket Analysis to Understand Adjacencies and Maximize Profits
For progressive retailers or those familiar with CPG analytics, analyzing basket adjacencies is nothing new. With basket analysis, you can narrow your focus down to a specific product or category, and see what products and categories are most likely to be sold with the original product. This is determined by analyzing the products that make up each individual transaction, looking at the total contents of each individual customer’s shopping basket. This allows you to understand how frequently two items are bought together, which then allows you to predict the most likely basket adjacencies for an item of your choosing.
Enough definitions: what else can basket analysis tell you and how can understanding basket dynamics help suppliers increase off-premise sales?
With basket analysis, you can determine what products are most valuable overall due to their likelihood of being purchased with high-margin items.
For example, if you are trying to decide between two products to create point-of-sale materials for, select whichever product is most frequently bought with items that offer a large profit margin to the retailer. If you see that Product A is frequently sold with 18-year old Scotch while Product B other is usually purchased with a 6-pack of light beer, even if you predict higher sales of Product B, promoting the other product will lead to larger revenue for the retailer, so they will have more incentive to stick with that promotion and merchandise that item favorably in the future.
According to a recent talk by Paul Hetterich, EVP & President of Constellation Brands Beer Division, entitled The Premiumization Wave: Using Data & Insights to Drive Growth & Change that discussed Constellation’s “Total Beverage Alcohol” Strategy, consumers that drink across all three categories (beer, wine and spirits) make up 55% of the share of dollars spent.
This customer is extremely valuable to suppliers because their purchases are spread across categories with varying profit margins, but also because they spend significantly more overall. In fact, the Dollars per Buyer of the Total Beverage Alcohol consumer is 7x more than a consumer of only one category. Therefore, items that are associated with cross-category consumption — appeal to the customers that are most valuable for both the retailer and supplier.
Understanding basket adjacencies also allows suppliers to begin understanding the consumption patterns and characteristics of customers for each of their brands.
Basket analysis can tell you how much customers of a certain brand are spending on average, the number of products they typically buy at once, and the specific products and categories that they are also likely to buy. You can then directly compare two products to see which is most likely to be purchased with 10+ items or as part of a purchase totaling $100 or more.
When developing marketing strategies, partnership programs or allocating budget for POS material, using basket analysis to better understand product dynamics and consumer behavior can go a long way.
Analyzing Individual Transactions and When They Occur
Another type of customer-focused data that is extremely valuable for suppliers to analyze is time-stamped transaction information. Knowing the day and time of a transaction is important for many reasons, which we will cover in future posts, but today our focus is the use of time-stamped data to improve scheduling of in-store tastings.
According to WineOpinions, 60% of consumers say that “tasted wine in store” is the factor that has the largest potential impact on a purchase decision, significantly more than seeing an item on a shelf or in an advertisement.
Tastings are one of the most effective ways for brands to drum up new business, reach new customers and showcase new products. Using time-stamped transaction data from a POS system to schedule tastings at the most optimal times is easy and can be done in a few ways, depending on your goals.
If you are trying to reach customers of a certain brand, simply schedule the tasting for a day and time that your analysis indicates is most popular for that product. If you are deciding when to schedule a tasting for a new scotch whisky you have released, start by looking at what times customers most frequently buy scotch in this store. Similarly, when trying to capture market share from a competitor with similar products, if you know when shoppers typically buy a competitor’s products, you can schedule tastings for exactly this time so you know their customers will be in the store.
In addition to optimizing the timing of tastings, looking at trends of time and date for purchases can also tell you a lot about how different products and categories differ. in the behaviors of their consumers. For example, maybe you have two similar products that have similar characteristics (i.e., category, price, proof) but the adjacent products for each are markedly different. This can shed light on the type of customer each product attracts and how they differ, and this intel can inform your marketing and sales strategies beyond this single off-premise retailer or market.
Instead of trying to get by using the same old depletion data you’ve been stuck with, shift the focus of your data collection and analytics efforts to the shopper’s perspective – what they’re buying together and when they’re buying it – and you will be able to understand consumer behavior like never before.
Adopting the customer’s perspective for data collection opens up a world of opportunity for those looking to understand the impact of factors like time of day/day of the week, basket adjacent products, and most importantly, the characteristics of the customers purchasing those items.
Analyzing customer-centric data such as this allows suppliers to understand and target the off-premise shopper in ways not previously possible, which is the most effective path to increasing off-premise sales.
If you are a supplier who is interested in leveraging customer-centric data and analytics to transform the effectiveness of your off-premise marketing and sales strategies, we at 3×3 Insights are here to help.