In a pre Covid world where 90% of all commerce happened in the physical world it is perhaps surprising so little of the data generated is being put to use. 

A lack of technical sophistication, legacy systems and commercial focus has made it extremely difficult for marketing service providers to tap this data and use it to drive consumer behaviour at scale

Despite the historical efforts of leading UK grocers through their own proprietary or coalition loyalty marketing programmes, the truth is that the retail market, as a whole, remains focused on other priorities, not data, as business owners fight daily fires in offering goods and services to their customers. 

A need to collect, clean, analyse and then action customer data, including the ability to measure the benefits & determine a ROI, is still very much a secondary consideration

Companies that serve merchants have in their part traditionally focused on activities that bear the most revenue.  POS vendors & Payment companies traditionally saw more money from non-data services meaning that the use of data was always seen as a distraction

Commercial pressures mean that this has now started to change. 

Driven by their on-line experiences, merchants are becoming more comfortable using data to better manage their customers.  Tech start-ups, especially in the mobile payment and loyalty space are showing merchants what is possible with improved data analysis and the impact this has on the bottom line. 

In the next decade new business owners will have grown up using technology backed by data and will expect far more sophistication from their providers

POS vendors have already started offering more added value features, investing development in data and promotional tools that have become ‘table stakes’ within the product specification.   As POS prices continue to fall due to lower POS software development and falling hardware costs the market will started to prioritise data revenues seeking out new revenue streams

This data revenue starts at the lowest level: syndicated data, delivering aggregate insights across market sectors.  

For example, syndicated data would tell you that product A sold more than product B last month.  Further filters on syndicated data could show you things like what regions product A performed best in, and at what prices.

As POS vendors start to discover that data must be cleaned and organized to grow in value, you’ll see POS product development changes that force merchants to more uniformly code their sales items. You might see standardization of menu items from drop down lists, so merchants don’t have the opportunity to abbreviate “chicken” or misspell “cheese” for instance on the sale of burgers with added cheese.  

From here, the value of syndicated data increases another notch where you can start to analyse discounts and promotions to determine if they’re creating lift on item sales.  This cycle continues as more item level data comes into the syndicated data pool and cleaner data attributes are added to transactions.  

At some point, however, the syndicated data market will reach its maximal value. To climb the revenue ladder more data must be added.  However, due to PCI compliance, the reality is that only payment companies have access to Personally Identifiable information coming from customer card transactions.  POS vendors responding to PCI compliance have dumped all customer card data effectively removing their software from the scope of PCI

Here is where the payment companies are brought into the data discussion.  Since POS companies are not collecting Personal Identifiable information they need to involve the processors or card networks to match transaction timestamps at the merchant check level with timestamps from the processing stream, thereby marrying the two data sets

Taking the data separately, here’s what you’re given:

POS Data Stream: Basket Data. Useful for basic syndicated data, but no POS vendor will pull this off independently. 

Processor/Network PII Data Stream: Customer Names, which can give you Demographic Data of interest to low-margin retailers who want to know their customers and where else they’re shopping but not what they are buying

Married together, the data taps into the high-margin advertising dollars because you’re combining item data (which suppliers care about) with demographic data (which marketers care about).

The key, however, is to make enough Basket Data and PII data be available across enough verticals and regions at a deep enough level to give advertisers confidence that the data is reflective of the overall market.  This is why SKU data is going to have to come from a multitude of POS vendors as no one company has enough to grab the big advertising dollars. 

When Payment Processors are made aware of these new revenue opportunities the big question is if they will simply buy POS vendors to access their data? And, if they don’t, there will be all sorts of new data driven companies in the mould of Google, Facebook, and Amazon to take advantage.