Relative to other industries, retail has been resistant to spending more on technology until recently. Who wouldn’t agree with that? However, today as customer expectations are growing and all retailers can think about is how to please shoppers, retail is actively looking for new technological solutions to invest in. Global retail sector technology spending is projected to reach some $225.4 by 2022. IT services are expected to account for $100 billion. At the same time, around 40% of businesses expect innovations to cut costs across various business processes, including pricing. Luckily, the market already offers some cost-cutting solutions which can help make up for growing expenses. One of them is a verified dataset, which allows for lifting a significant financial burden off your IT department’s chest. How exactly does it work?
Saving money on data verification
Smart pricing decisions require data. However, just the fact of gathering market intelligence is insufficient. What’s the point in collecting competitive data if it is not complete, accurate, and timely? Low-quality data leads to ill-informed decisions and eventually costs retailers significant dollars — that’s a no-brainer. At the same time, companies have no choice but to react to market changes immediately and properly using whatever data they have — otherwise, they give their shoppers to their competitors on a silver platter. As a result, retailers are looking for a way to make sure their data is reliable.
To ensure that they have a verified dataset, many retail businesses roll out an internal data quality control system. This is the case regardless of whether they collect market data with the help of an in-house solution or partner with a data provider. Launching and maintaining such a system costs a lot and requires the constant involvement of the retailer’s IT department. As a rule, engaging the IT department translates into growing expenses. What is more, as usually, IT professionals are not intimately familiar with the peculiarities of the industry, very often the solution which they put forward does not meet all the constantly changing requirements for such a system. Meanwhile, external data providers already guarantee a 98% accuracy, with up to 12 data updates per day. Some companies even let retailers verify data manually in just one click.
Checking the data quality on the side of a data provider is a time and money saver. “We have saved 70% of the IT budget, or the capacity of three full-time IT professionals, for data scraping and validation. The price scraping software we are using helps us get reliable, timely and accurate competitive data,” says a representative of the Eastern European online retailer Ulmart that has partnered with one of such providers, namely Competera, to receive the data.
Is the data about competitive prices the only advantage of partnering with an external data provider? Technology has advanced significantly throughout the past years and retailers can get as a diversified dataset as they wish: literally every bit of data presented on the product page.
Getting high-quality data about similar products
Meanwhile, when it comes to data quality, accuracy and completeness are not enough. Many mature retailers need to get the data not only regarding so-called exact matches (when you compare exactly the same products which dozens of your competitors can be offering), but also regarding similar or alike products. Items which are unique like private labels or new to the market, differ from otherwise similar goods by minor characteristics such as color or have unique model numbers for each distributor qualify for similar products. Although they can make up to 30% of the assortment, in most cases retail companies still have trouble monitoring and setting the right prices for them. The good news is that today businesses have several options to choose from to address this issue.
Private labels account for a lion’s share of the assortment of Eastern European omnichannel DIY retailer Sdvor. According to Natalia Guseinova, pricing manager of the retailer, the company is doing well when it comes to pricing such items. Partially, thanks to cooperation with an external data provider. “Sometimes we need to find close matches for our private labels. Unlike other retailers, we make our own products from high-quality materials and do not sell them cheap. Therefore, it is not enough to simply browse any website for a similar product at the lowest price — we need to find a match for every characteristic of the item to position our product properly.”
The retailer has been using a separate module allowing to match products by minor attributes. A category of lookalike products is added for each competitor to monitor their price, promos, stock and other essential factors. Among the results of such cooperation are tenfold operating cost savings, as well as accurate and fast manual repricing of KVIs.
Thanks to the booming innovations, gathering and verifying the data about look-a-like products on the side of a provider is not a novelty anymore. Retail giants like Gap warn: tech-resistant companies will be off the market in a matter of years. However, innovations do not have to be hard to get. Today retail companies can save time and a significant portion of their budgets by outsourcing everything but what constitutes their competitive edge to a third-party provider and grow rapidly and seamlessly.
Alexandr Galkin, CEO & Co-founder of Competera, price optimization software for enterprise retailers looking to increase revenue and stay competitive. Forbes Technology Council member, speaker at IRX, eCommerce, RBTE conferences.