4 Ways to Analyse Your Point-of-Sale Data

1. TREND DATA – to leverage time variations in POS data for different perspectives

The big advantage with retailer POS-data is that it´s near time data. This allows for a flexible, customizable views of time periods and a truly data driven approach. With near time data you can conduct both trend analysis as well as daily analyses and even hourly results in some cases.
It is important for suppliers to monitor results through effective reports and scorecards. Make sure that you are looking at both shorter- and longer-term trends when looking at your business. Shorter-term trends can proactively help you to fix issues before they extend into longer-term trends.

2. OUT OF STOCKS – to determine stocking issues at store level

Out of Stock (OOS) lost sales are probably one of the most difficult things to measure and act on. Weekly or even daily sales data with significant gaps would be a strong indicator of OOS issues, as would a significantly underdeveloped market share combined with full distribution. Looking at weekly or daily data with sales gaps illustrates the power of near time data and allows sales reps to act where it´s the most needed. The big advantage with POS-data compared with syndicated data such as Nielsen when it comes to distribution is that it´s near time data, it´s at that unique store and it´s actionable information for the sales rep.

3. SALES ANALYSIS – to understand brand, segment, category, department, and total sales results

In addition to standard sales measures like $ sales, unit sales and profit, retailer pos-data also allows you to track Same Store over time and even compare between stores within the same sales district. Historical sales data allows Sales reps to compare this year’s sales in the store to the same period last year or even the previous sales period. These measures allow Sales reps to gauge how effective their programs are at driving organic growth in that unique store and how to improve sales going forward.

4. DISTRIBUTION ANALYSIS – to track new items, product availability and product assortment 

Tracking new items can be done easily and accurately by creating a report that tracks the percentage of stores selling an item. Here, distribution would only be recognized once the first sale is recorded. Retailer pos-data is faster and more accurate compared with scantrack data such as Nielsen and allows the whole commercial organization to have the right focus on the novelty.
The “% Stores with Sales” measure captures the percentage of stores that carry the item. An analysis like this gives a perspective on how quickly product is getting through the supply chain – from the warehouse to the store’s receiving, then out from the backroom and onto the shelf. It also allows you to quickly understand which stores not yet selling the new item and to take swift action in those unique stores to close the distribution gap. This is crucial way of working to build penetration and create trials as fast as possible for the new item.

Retailer pos-data can provide compelling insights. Because all your categories are available all the way down to an item level, the analysis capabilities are unlimited! Scanned pos-data allows for powerful, flexible analysis, including in-depth promotion, pricing, assortment and novelty analysis.

Looking to build your point-of-sale analysis toolkit? CatMan Solution can help you, your team or your organization learn more through a single source of truth with a customized set up for your organization. We have some great intuitive and interactive category management best practice reports and dashboards available in power BI to meet your needs.