The Death of Traditional Price Monitoring

The rise of online and mobile shopping brought with it a rise in price transparency that drove many retailers to adopt competitive price monitoring practices.
Companies put together teams of individuals and vendors to help them get pricing data, which worked in some cases and didn't work in many more. These traditional solutions were good for strictly monitoring prices, but not so much for applied and active decision-making because they lacked accuracy, scope and speed.
These outdated price monitoring methods, tools and their results are inadequate for today's "always on" consumers and their expectations. With so many options and the ability to buy from whichever retailer they like at the click of a button, the customer is king, and retailers must push the envelope to understand what consumers want and what prices they are willing to pay. This abundance of rich consumer data is causing the death of traditional price monitoring.
Consumers expect pricing to remain competitive in real time. If they're in your store looking at competitors' prices on their phone, they will not wait for you to become aware of the competitive change when dated pricing method kicks in and alerts you tomorrow.
Enter smart price intelligence – which is about systematic, accurate and actionable pricing information. Newer technologies and methods now exist to arrive at accurate, timely and real on-demand price intelligence like never before. This, supplemented by analytics models powering recommendation engines, helps drive extremely smart, proactive pricing actions.
Unlike price monitoring, modern pricing intelligence is actionable. Retailers now have access to interactive dashboards that they can use to monitor prices and to set up flags to identify whenever a pre-determined set of circumstances necessitates their own strategic price adjustment. They can also set up custom rules that are specific to things like product category or geography, which can be based on everything from simple price changes, to percentage price drops, price hikes, web traffic, competitive price elasticity, and category-wide changes. Reactive price adjustments are often backed by learning algorithms that provide pricing insights and recommendations to optimize key variables including sales, margins and inventory levels. Retailers can install any number of rules to drive automated actions that align with their company's strategy.
There is also a good case to be made for employing live pricing analysts. Web crawling alone can only produce information to a point. All retailers do not describe their products identically nor provide the same type of information, so it can be very beneficial to have analysts to verify the data.
Deploying the latest price monitoring technologies can be useful not only in setting prices, but also for assortment decisions. Being able to leverage democratic data (i.e., free, open data available to all across the internet) to uncover the "state of the union" in terms of what competitors are carrying and what consumers really care about can be a critical piece of ensuring the best possible revenue and profit margins.
There is a paradigm change in what product data is being captured, how it's being captured, what methods and techniques are being used to process, understand and synthesize the data, and what models and tools are being deployed to drive the price change. It's a paradigm change from a passive approach to an active one. Failing to embrace this can come at a huge price – the permanent loss of your customers.
Mihir Kittur, co-founder and chief innovation officer at Ugam Solutions.