The future of retail - intelligent data personalisation

According to all the figures that are being released by the top four banks and the Australian Bureau of Statistics (ABS) it looks as if the recent interest rate cuts and lower petrol prices have assisted retail spending. February saw a 0.7% month on month increase in retail spending and January a 3% increase from the previous year. The correlation between these increases and the spending in categories associated with strong housing market is obvious with a 1.8% increase in household goods.

Although these figures look good, it’s not until you compare them to the online figures that you understand how relative they really are. The online retailing sector has seen a comparison year on year increase of a whopping 8.7% with many sectors having a decent jump.

Results aside though, the trend of unpredictability from the retail sector makes it a very unstable environment to build a wildly successful retail company using only the traditional bricks and mortar store. With multiple mediums and methods in which retailers can now interact with their audiences, many retailers are improving their conversion by turning to ( and investing in ) the infrastructure required to not only communicate effectively but also, more than ever, personalise their message. 

Data is key to true personalisation

The best way I can explain personalisation is to draw a parallel with something that I am sure many of you have had some experience with in the past – mail merge. Mail merge allows you to create fields that can be inserted into a personalised email or letter to give the impression of a more targeted or individual communication. 

A study by the University of Texas showed that as humans we desire personalised experiences (or engagement) in online environments because of two factors: the hunt for control and the friction of information overload. In a nutshell, if we feel like we are getting an experience that is personally tailored we not only have the illusion that we are in control but it also feels that we are filtering out unnecessary information and therefore making it a quicker and cleaner experience. Although much of this remains an illusion for the customer it creates a positive attitude towards the product and brand while also (hopefully) creating a faster journey to sale.

4 ways data can personalise your customer experience and improve productivity

In the infancy of true customer personalisation, many retailers were using simple systems to tag their customers for more effective marketing efforts. It is only with proper centralisation of all data however, that the glory of a true omnichannel personalised experience can be truly fulfilled. Below are a few examples of what can be achieved by a centralised approach to customer and operational retail data.

Simple In-Store Conversion Ratios

With the release of more and more store traffic counters that can connect to the internet, there is another, previously manual, puzzle piece that has been added to how retailers measure their success. The main difference being how quickly they can pivot based on fast data. Clients are using data aggregators like our systems to sync appropriate information from the Point of Sale Systems and store traffic counter, calculate the conversion ratios and finally trigger workflows to create necessary alerts. This allows them to quickly pick up and act on “red flags” like:

  • Toxic management or staff
  • Training gaps
  • Effectiveness of new customer service policies

Website regional personalisation

Every day retailers are collecting market, sale, traffic and accounting information and making very manual e-commerce decisions based on the priorities in their online channel.

New dynamic personalisation technology allows the “on the fly” modification of a website based on the analytical data of the user that is viewing it. For retail, this functionality can allow information gathered from another channel (eg: top sellers of a particular region of stores) to dictate what should be shown on the website for users visiting from the same area using IP pin-pointing (eg: change banner image for the visitors in this area to show top selling products in that area).


Many of the decisions made by the Visual Merchandisers of stores has a lot to do with the seasonal products that are new and predicted to be good sellers – not what the store visitors want or even are actually buying.

“Me-Mechandising” allows analytical data to be pulled from all the apps in all channels make sufficient calculations and then recommend the most appropriate merchandising to put in store windows or near the counter. Things like:

  • Which category of products sell the most
  • Seasonal Clearance stock based on external influences (school holidays or end of Winter)

Store web ownership

The true connectivity of data also allows retailers to improve productivity of staff too. We have recently successfully connected a major retailer’s website with their branches of Point of Sale Systems. This allows the system to automatically locate the nearest store to the customer and then have that sale “pop” up in the POS system of that store for full processing. What this allows is a more dedicated customer service approach while also increasing the productivity and conversion of each store. It also allows the reduction of stock in the warehouse.

To summarise, we are seeing a new age of data driven artificial intelligence in the retail sector. From a consumer level, it is not something to be feared. With every improvement in personalisation, the retailer improves how directly they communicate with you and in-turn fast-tracks you to your desire outcome – the right product at the right price. 

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