The recommendations your customers really want

shutterstock_323602631Guy Marson, co-founder of data science and intelligence marketing company Profusion, discusses how data sources can be used to give your customers better recommendations.

Beacons and wearables are revolutionising the way retailers tailor in-store experiences and preferences through personalising consumer recommendations. With millions of options available to customers, highly targeted marketing initiatives have become more and more essential. A whole host of technology has been invented to fulfil these needs. It is no longer necessary, for instance, to walk into a changing-room to try on garments; with the introduction of interactive mirrors, you can now try on clothes virtually.

Savvy retailers, eager to capitalise on this trend, can draw on a wealth of data to inform them about exactly what products to offer their customers. You can find out what your consumers really want in a number of ways. Marketing surveys, social media data, purchase and in store activity (via beacons) and information from loyalty cards are all valuable sources revealing what your customers potentially think. Marrying this data together and using data science can identify trends that are not immediately apparent from a cursory analysis of the information.

A perfume company, for instance, could suggest perfumes a customer may like to consider in the future based on the reviews that a customer has given on their current products, what they have bought previously and what they have looked at online, as well as external data, such as weather, economic trends, location and socio-economic factors.

The more data you have on your customers’ interactions with your brand, the more insights you are likely to achieve. Data scientists can create bespoke algorithms that match any business’s size and objectives. Using a range of techniques, recommendations are devised to meet individual preferences. Once set up, the engine optimises consumer modelling by adjusting consumer recommendations based on the new data it receives. Outputs from the engine can then be presented to consumers using the interface and other personalised marketing initiatives.

Data is then stored securely, synthetized and analysed to provide an accurate shortlist of influential drivers to purchase. Crucially, the larger the data set the more accurate the results.

Streamlining recommendations increases sales and raises conversions as well as improving customer satisfaction by attending to customers’ specific wellbeing needs. You can also understand your customers more effectively by studying how they choose products and interact with your brand. Transactional data and information on what a customer has clicked on online can be used to tell you what they are potentially interested in. Knowing this information gives you an opportunity to market products relevant to a specific person at a time when you know it will be relevant to them. This is the holy grail of marketing, delivering a personalised message to a highly targeted audience at a time where they might even be thankful for the promotion or information you’re offering.

Using your customer data also allows you to ensure your marketing budget is allocated appropriately. More targeted recommendations can also make marketing campaigns more effective, preventing superfluous messages being sent to customers that are not in line with consumer preferences.