The Data Dilemma with Retail Pricing and How to Untangle it

Making the leap to something new can be daunting. Like running a marathon, some may never take the first step if they find the training involves nearly a year of training, the right type of shoes and a schedule that will allow for big chunks of the week to run and work out.

Unlike a marathon, pricing shouldn’t feel as daunting to kickstart, no special running shoes needed or a major time investment. In fact, there’s no reason you should be missing dinner any night of the week to deal with the data dilemma when it comes to pricing. In my experience, the data is what keeps retailers from making the big jump to new pricing technologies and strategies.

I’m an avid runner so naturally I’ve made this analogy, and it’s a great one to describe to retailers who are mired in the minutiae of pricing — especially as the market fluctuates in year two of the pandemic while Amazon makes a different move to any SKU multiple times a day and the supply chain is riddled with hiccups in every link of the chain. 

Imagine the possible repercussions if you don’t have a good grip on your data affecting pricing. If you’re in doubt, read along as I share the top five questions I receive from retailers on data and pricing and how I recommend each question is approached.


1. How much data do I need to shift support and drive my overall pricing strategy?

Just like making a move to be healthier or start exercising, with data, starting small can make a huge difference. Take the crawl, walk, run approach as you begin. I recommend to first test a business unit, a region or a category to see what insights can be derived from the data you have. 

2. I don’t have all the data I know I should have, is that OK?

Many retailers are worried that they don’t have all the data at their fingertips, like product data, customer data, transactional data, when items sold, on what device and more. Everyone starts somewhere, and it’s OK wherever you are at in your data journey.

Begin with what you have and build a plan to fill in the gaps. Many of your retail peers found themselves with the dilemma of missing data — from the lack of customer data, transaction history for certain items or timeframes or sales broken out by sales type (regular/base, promotion and markdown). I assure you that not every retailer has this all, and this should be expected when you’re looking for a better pricing strategy. This is your starting point and your job is to build up and improve it.

3. Do I need competitive data?

For example, does Home Depot need to have data on hand on what Lowe’s is doing for every SKU? I recommend collecting competitive data, at least as a reference point, if not a driver for adjusting your retails. I would take a guess that you are already doing this. 

If not, you don’t have to collect every SKU, every day for every competitor location or web page. Start with the items you and your customers deem most important (KVIs – Key Value Items). Your buying teams and supporting staff can do this, or there are many great webscrape or in-store price collection teams that can help as well.

4. Does my data need to be scrubbed?

Clean data is great to have and the cleaner it is, the better. But just like exercising, if you can’t run as fast as the other runner, can’t do as many pushups or don’t look as good with a swimsuit on, it doesn’t mean it’s a worthless pursuit.

Data is a journey, and continuing to cleanse, augment and challenge it is part of the process. Think of it this way; even the folks you see at the gym who are fit are still working on their fitness. Everyone is working toward a goal, even if others seem further along in the journey than you. Retailers should always strive to have clean data and go through the process of watching their data closely, make sure it’s clean, and ensure it’s clean moving forward. 

5. Who do I talk to about my data?

I recommend you talk to a ‘trainer’ before you begin. If you are unsure of your next steps, find a peer, industry expert or partner to help assess and utilize your data to its fullest. You will be pleased to find new pricing strategies and the different ways that data can be used to give you a competitive edge.

John Gilbo is an Enterprise Account Executive at Pricefx, where he puts into practice his deep experience in pricing strategy, client account management, software procurement and implementation and financial analysis. He formerly led pricing strategy at Kirkland’s, Academy Sports + Outdoors and Safeway, where he was hands-on with AI-based analytical tools, retail strategy and change management. He is also an avid marathon runner and triathlete.

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