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How Retailers Can Leverage Big Data for Competitive Pricing Insights

, | March 17, 2017 | By

by Bob Lambert – 

Are you taking advantage of the opportunities Big Data provides for monitoring your competitors?

If not, you could be. And you should be. After all, you can be certain that at least some of your competitors are keeping an analytical eye trained on you.

In fact, a recent survey of leading retailers revealed that 100% are utilizing some form of competitive data in making pricing decisions. But far fewer retailers are using Big Data: less than half said that they use three or more types of competitive data in making pricing decisions.

Keeping an Eagle-Eye on the Competition

Retailers have always kept tabs on the competition. Monitoring advertisements and strolling through stores are among the many low-tech ways of monitoring competition that have long been in use.

Back in the day, these low-tech monitoring techniques were the only means available for keeping abreast of the competition. But not any longer. Technology has changed the game.

Now, for each of your competitors, you have available to you potentially trillions of records of data. And you also have available to you the technological capability to store and process that massive amount of data.

You can use these tools/data feeds to enable real-time monitoring of your competitors — not just what they did last week, last month, or last year, but what they’re doing right now. Big Data analytics that yields real-time insights provides the ability to:

  • Identify profitable prices that achieve strategic and financial objectives
  • Forecast and measure the impact of price changes
  • Automate the pricing process to ensure consistency of price image while eliminating manual, error-prone tasks
  • Execute competitive positioning while maximizing profit opportunities
  • Simulate real-time “what-if” scenarios for predicting alternate strategy outcomes
  • Localize prices based on shopper demand and competitive behavior

Despite the many potential benefits, 75% of retailers do not use real-time competitive analytics. Those that do can gain a significant competitive boost.

Comparing Apples to Oranges

Big Data analytics also gives you a new and very important asset: the ability to compare disparate types of information.

The data available to retailers today consists of a vast amalgam of different types of data, including structured and unstructured. Product-specific data is just a subset of that ocean of data; many varieties of non-product data (weather data and customer sentiment data, for example) are also very important.

We can use the science of data analytics to tease a variety of usable, actionable insights from that vast wealth of data, including:

  • Prescriptive Insights: Reveals recommendations as to the type of actions that should be taken
  • Predictive Insights: Forecasts scenarios that are likely to occur
  • Diagnostic Insights: Analyzes what happened in the past, and why
  • Descriptive Insights: Provides a ‘what’s happening now’ viewpoint based on real-time data

The goal of competitive price analytics is to determine the best action to take. And that best action won’t always be lowering a price. Sometimes the most beneficial move will be to raise a price or to hold the price to its current level.

The insights resulting from analytics that compare disparate data types can help to define that most beneficial action.

Alert! Alert!

A key benefit of Big Data analytics is the ability to generate real-time alerts. Alerts can help your company quickly react to competitors’ significant price changes. Alerts can serve as an effective tool for establishing your company as a market leader instead of a market follower.

Alerts are also helpful in:

  • Aligning prices with sales and marketing focuses
  • Testing loyalty in specific markets
  • Testing competitors’ reactions to your pricing in designated test market areas

Kevin Sterneckert, past Gartner VP specializing in merchandise life-cycle optimization, noted that “…it is imperative for multichannel retailers to be opportunistic and flexible with their pricing so they don’t miss opportunities.”

The alerting capabilities of modern data analytics tools help to assure that opportunities are not missed.

How It’s Done

Deriving competitive pricing insights from Big Data should be a very structured process.

But it’s important to note that the process should be selectively applied; it’s unlikely that you will benefit from performing competitive pricing analyses on every product in your inventory. You’ll want to focus on products that serve as the foundation of your business.

An overview of the competitive analysis pricing process can be summarized with the following seven steps:

  1. Prove Automation Potential: Though most everything can be automated these days, it’s still important to verify that the procedures and processes you’ll use for price monitoring are adaptable to automation.
  1. Validate Sources: You want to be certain that the information you’ll be feeding into the process is consistently accurate and properly focused.
  1. Develop Instant Insights: Consider creating applications that make it easy for employees to instantly pull up real-time pricing data from competitors. (This capability is most likely to be used in the event of customers questioning whether your pricing is competitive.)
  1. Gather Feedback on Performing and Non-Performing Locations: One of the most significant benefits of performing competitive pricing analysis is the location-specific insights generated. This form of insight can be of tremendous value for retail chains — even driving decisions as momentous as determining whether a given location should be closed, remodeled or moved.
  1. Determine Strategy Violations: Define reactive strategies. Strategies should not be as simplistic as simply lowering a price every time a competitor lowers a price. Strategies should enable and enforce the consistent deployment of the most beneficial action based on your product’s sales strategy.
  1. Formulate Basis for Clearance Planning (markdown plans): Incorporate long-range planning in price-lowering by matching competitors’ actions. For example: Will lowering the price on a given item deplete inventory too quickly?
  1. Visualize Non-Standard Seasonality: What has happened in the past with a given product during a given timeframe? Perhaps you’ve consistently enjoyed a ‘bump’ with this product during a particular season, making it counterproductive to lower the price on the product during that time of year, or around a significant selling event.

Is Your Price Right?

Throughout the history of retail, getting the pricing right in response to competitors’ pricing has always been important. And it’s certainly no less important now. But the tools available for getting your pricing right offer previously unimaginable capabilities and insights.

Recent research has shown that  “…price management initiatives can increase a company’s margins by 2 to 7 percent in 12 months — yielding an ROI between 200 and 350 percent.”

So if your company is not taking advantage of the capabilities of competitive pricing analytics, that begs a very obvious question: Why not?

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