THE SALES EQUATIONS Data-driven retail and neuromarketing
Each year sees the publication of reports on the retail trends in store for us over the coming months, such as those published by Price Waterhouse Coopers and TNS Retail.
Image: Carla Vallès
At the start of 2015, one forecast on which most of these reports are in agreement is the consolidation of data-driven marketing (Honaman, 2015). Applied to retail, this involves using business data to be able to carry out actions, such as special offers, for a particular customer based on their location in the store, whether through screens or the customer’s own smartphone. This can equally be applied to physical and digital stores.
Such personalized action activity is based on the use of technologies such as multimedia installations fitted with cameras to detect the sex and age of approaching customers, instantly showing them a promotion adapted to their profile on the screen. The other technology underpinning such initiatives is currently growing in double figures and is paid for by the customer: their smartphone, linked via Bluetooth, iBeacon, NFC (Near Field Communication) and, logically, the CRM.
The sales equation
The usual method of quantifying sales in a physical store and estimating potential growth applies the following parameters:
- Size of the scope of influence.
- Number of people of the main target segment.
- Achievable market share, taking the competition in the area into consideration.
- Frequency of visit.
- Conversion rate (% of visits that end in a purchase).
- Average purchase (= quantity of products x price).
The last of these parameters should be broken down into two parts, depending on the customers’ behaviour:
- Items they planned to buy, that were on their ‘shopping list’.
- Unplanned purchases. The relative weight of this part varies significantly depending on the sector and retail format.
It seems clear that many of the aforementioned technologies tend to focus on this last part of the equation nowadays. Lindsey (2014) also confirms that the majority of inter-related technologies on which data-driven retail is based are highly focused on increasing impulse purchases.
Most people know that the vast majority of human decisions are subconscious or implicit, activated by the limbic system, one of the fastest parts of the brain which, paradoxically, consumes the least glucose. The cortex, the part of the brain that activates when we do something consciously, is much slower and consumes a lot of glucose.
When we do the shopping, we pick out the planned items almost semi-automatically. However, when an offer catches our eye or we get a promo message on our smartphone, we switch from the ‘automatic pilot’ of the limbic system and turn our newly-activated attention to the message we have received. This is when the cortex kicks in, meaning that we are making a mental effort, as we consume more glucose that just a moment earlier.
As Dr. Ralf Ebert explains, when somebody makes effort while shopping, the same part of the brain is activated as when we suffer physical pain: our brain interprets it as an implicit pain. For this reason, when we ask for customers’ conscious attention, it must be compensated for with a relatively large reward (for instance, a real bargain or a moment of happiness).
Customer loyalty is quantifiable
It is well-known that customer loyalty is one of the two founding pillars of the retail business model. Nobody can make a living from customers that buy just once. We want and need them to keep coming back and purchasing repeatedly.
As such, in other words, the company must perceive itself not as a seller of products or services, but rather as a customer cultivator.
This can be quantified. The measurement for calculating the value of a specific customer over the long term is the Customer Lifetime Value (CLTV) or, to put it another way, how much each customer is worth (in € or $) if they continue shopping with the same pattern and habits as they have done so far.
On the following website, Harvard Business School has developed a simple tool for simulating CLTV.
So, how can we stimulate loyalty? Many people think that the key is a fascinating and highly sensory shopping experience. However, one study (Dixon, Freeman and Toman, 2010) shows that customer loyalty is achieved more effectively by reducing the efforts they have to make while shopping, providing what could be referred to as a friction-free shopping experience.
Do these trends work against customer loyalty?
If enhancing the sales equation involves tiring out our customer’s brain, we need to get rid of any unnecessary loads on this journey. To put it in a more contemporary way, if sales are encouraged using ‘push’ promotional strategies, tired out customers may stop coming to our store. This is what many tourists end up doing, crossing the street to avoid waiters who stop them to persuade them to enter their restaurant.
To avoid such problems, the following seven tips may be of use:
- 1. Interlinked with the CRM, commercial and contextual data (weather, events, etc.) represents a powerful source of opportunities for gaining greater understanding of the customers, to later be able to implement suitable actions to grow the business. Market intelligence is a key part of any good marketing and sales department.
- When we do the sums, the CLTV is greater when customers keep coming back to the store, despite their average purchase each time being lower.
- Take full advantage of the fact that smartphones know their owners’ context (space and time) so that they can receive offers adapted to their present situation.
- Avoid excessive promotions or communications that force customers to pay too much conscious attention. If we fail to do so, we contaminate the store and cause their psychological self-defence mechanisms to kick in.
- Whenever we want to grab the customer’s attention, we have to offer them some kind of reward by way of compensation.
- As far as the customer’s brain is concerned, one strong promotion is far better than twenty weak ones.
- The rewards must be relevant. In other words, if we possess customer data, we have to be able to offer them something that is truly adapted to their needs. There is no point sending them a promotion for nappies if their kids are all grown up. If we do not manage this, the store may be seen as rude or, even worse, irrelevant to the customer’s life.
- Price Waterhouse Coopers & TNS Retail (2007) “Retailing 2015: New frontiers”.
- Honaman, J. (2015) “Top 6 retail trends to watch in 2015” in Retail Info System News, 5th January
- Lindsey, K. (2014) “Sealing the deal: Six digital tools targeting impulse shoppers” in Retail Dive, 27th May
- Dixon, M., Freeman, K. & Toman, N. (2010) “Stop trying to delight your customers” in Harvard Business Review, July.
Source: Código 84, number 185