Walmart Suppliers have two significant sources of Big Data (at least): Retail Link, which gives insight into sales in Walmart and Sam’s Club stores, and Google Analytics, which gives insight into visitor behavior on the web. You might use another web analytics tool or a different shopper insight tool, but you can still get more out of both tools if you consider how to use them together.
Most don’t. Marketing looks at the web analytics and managers look at Retail Link, and that’s often as far as it goes.
Yet 86-96% of consumers (depending on your product) will go online for information before they shop. Seeing a rise in interest in a product at your website gives you a bit of advance warning — and should be followed by a bit of a rise in sales of that product. Seeing when a product’s online visits began to rise and fall last year gives you a great heads-up on seasonal interest. Seeing a peak online that doesn’t lead to increased sales tells you about missed opportunities.
How can you harmonize the two?
- Plan your website and set up your analytics so you can measure some of the same things. If each product has its own page, you can measure interest in an individual product. If you wonder whether people will buy your product for a particular holiday, you can write a blog post about that and get a fast indication of how much interest the idea might get. If you set up goals, you can track activity from particular geographic areas or particular traffic source.
- Look at similar information in both. Often, people will look at traffic or unique visitors in Analytics or sales in Retail Link and leave it at that. However, both Google Analytics and Retail Link give you geographic information. Look at both and see how the data compares. Watch for patterns in the data and you can improve your forecasting.
- Distinguish the signal from the noise. In both cases, you have access to enormous amounts of data. The connections may not be obvious at a glance, because there’s just too much going on. Try formulating questions. If you see that sales in Retail Link varied from predictions by 25%, look in Google Analytics to see if you can find clues to the reason for that.
Here’s an example. You see a spike in sales of a your raspberry vinegar. Market Basket tells you that your vinegar sold along with chicken more than usual during that spike. Check analytics for the same time period — there’s a spike in traffic from Pinterest. Track it down, and you see that a recipe using your raspberry vinegar to make a sauce for chicken went viral. You might never have caught that — but not only can you repeat it once you see it, but your buyer will also be impressed by your explanation of that spike.
It will sound so much better than… “Yeah, I know we’re down in sales but it just was unusually high last month. Weird.”