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eCommerce Competitive Intelligence: Never Print a Screenshot Again

Data. eCommerce. The two terms might as well be synonyms: You can’t sell something online without providing and capturing information. Internal data sources are critical. Yet somehow, external market data is largely ignored despite its potential value to an organization.

In the past 20 years we’ve seen rapid growth in the use and availability of eCommerce data sources—web analytics, customer databases, merchandise information, revenue systems, and more.  However, if you step back and evaluate, you’ll notice an interesting trend. The vast majority of those data sources are internally focused. They’re limited to one company: yours. Your website, your customers, your content, and your data. When it comes to capturing data about competitors or the marketplace as a whole, things look like a 1990s redux. Monday morning screenshots, manual entry into spreadsheets, and folders full of mismatched files are still the norm. We’re all still in the dark ages of external data.

Why is external data so hard to obtain? In an age where changing the color of a banner ad is considered a big decision, there has to be a reason such a potential gold mine of information is largely ignored. Turns out there are several reasons external data is very difficult to gather.

It’s Time-Intensive and Time-Sensitive

Here’s an Excel file: capture every product Kitchens & Sinks sells. Even your rockstar intern would groan in dismay. If she spends the requisite three months cursing spreadsheets, it probably won’t do much good. A sound analysis is based on the change between two points. eCommerce sites change rapidly, so that poor intern would have a fuzzy view of different products, varying prices, and changing promotions.

You Need it all, but You Need to Be Specific

Unless you have all the data in a single category (or the website as a whole), high-level comparisons aren’t possible. It’s also impossible to compare individual products without their specifics, especially if they are private label. As already mentioned, the time needed to collect data increases exponentially if considering prices, product attributes (like availability, brand, capacity, etc), pictures, and promotions too.

You Need to Compare Apples to Apples (Normalize the Data)

Is that a coffee maker, an espresso maker, a milk frother, or all three? Every website has its own perspective on how products should be categorized. It’s a tall order to resolve those opposing viewpoints, even if it’s just a one-off assignment.

Manual Processes Are Error-Prone and Inconsistent

Humans make mistkaes mistakes. Even more importantly, they don’t capture their own “mistkaes.” We also tend to go on vacation, have dentist appointments, and occasionally do things more important than remembering to enter lines in a spreadsheet every single day.

So why go through all the effort? Like its internal data counterpart, external data is incredibly valuable. Let’s run through a few of the possible applications to demonstrate what to look for and just how powerful it can be for your company. For manual data capture, the key is specificity: choosing the question you are hoping to answer and focusing on collecting the smallest amount of data needed to do just that. We’ll discuss product, price, promotion and place.

Product

The ideal data set: a record of every product your competitors sell in a discrete category along with main attributes, descriptions, and pictures. Multiple snapshots of that data over the period of time that matters to you.

What’s possible:

  • Optimize your product assortment by highlighting strengths and weaknesses in your portfolio.
  • Analyze competitors’ assortments to understand what’s working for them, what isn’t, and what their strategy is.
  • Monitor the marketplace: identify who added new products (and what they are), differentiate your offerings, and see how products are being presented.

Price

 

Note that price is the easiest of all data sources to gather, but it is the least valuable data source in isolation. For example, a price disparity might be because of assortment changes, new promotions, or repricing software. With price data alone, it’s impossible to know.

The ideal data set: the prices for every product your competitors sell, with different snapshots over time. The important thing here is the actual prices in the cart, not just on the website.

What’s possible:

  • Know exactly where you are in the market. It’s hard to implement a “lowest price, most products” strategy if you aren’t certain of your position in the market. Know the full range of prices over time and how you fit into the mix.
  • Monitor MAP compliance and get the best deals for your buyers. Know exactly how much everyone else is selling your products for.
  • Understand why sales moved (up or down) during a specific period. Did someone drop prices, apply certain promotions, or introduce a hot new product?

 

Promotion and Place

The ideal data set: a record of each promotion from every location that a company releases them (over time, as always). Their homepage, email, tweets, etc.

What’s possible:

  • Know when and how to begin holiday/big event campaigns based on how your competitors did things last year.
  • Understand what methods and techniques work for your competitors by examining frequency and proportion of marketing spend.
  • Know exactly when and where to release your materials so you’re not directly competing (or are directly competing!) for the mindshare of your customers.

 

 

The Tip of the Iceberg

If you read closely, you’ll notice that the truly important pieces of analysis don’t come from the four concepts in isolation. By combining product, pricing, and promotion/placement data you can find answers to a far greater range of questions than you might expect. With a data set this big, there are a million ways you could slice it. The list of applications is as exciting as the information itself.

There is another name for “external data”—eCommerce competitive intelligence. This is what we do at Wiser. We’ve combined data science, crowdsourcing, and big data storage to capture the highest quality of data possible. We also created our own analytics application that makes getting the answers to these questions as simple as logging in. We look forward to helping you see what competitive intelligence can do for your company.

Contributing Writer: Baxter Roberson

Min-Jee Hwang

Min-Jee is the former Director of Marketing at Wiser. She has extensive experience working with SaaS companies and holds a BA from Carnegie Mellon University and an MBA from NYU Stern.

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