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ARTIFICIAL Intelligence (AI) is the current tech buzz phrase.

Greg Clark, Secretary of State for Business, Energy and Industrial Strategy has targeted AI to deliver an additional £232bn to the UK economy by 2030.

So how do you get started on gathering the data that can deliver the insights needed to generate more interest in, and ultimately sell, more vehicles? 

It’s clear that for AI to work you need to build online engagement with existing and prospective customers. The retail sector has already been quick to exploit the many benefits from AI. Notable examples are: 

  • Amazon, an early adopter of AI, reports that over a third of all sales are driven by its machine-learning powered recommendation algorithm. 
  • Netflix reported recently that 75 per cent of its 125m+ subscribers’ content downloads are down to its AI-generated personalised recommendations. 

AI specialist agency Peak.ai helped deliver a 27% increase in sales for digital car management services provider Regit.

Regit uses a driver’s registration number to provide him or her with reminders such as MOT, Tax, Insurance and recalls via their communication channel of choice. 

Regit came to Peak with a problem – they were unable to predict which users were likely to change car or even know which ones had changed cars until after they’d already switched.

Peak set to work – pulling together Regit’s user data with data from Peak’s website and marketing systems, as well as from the DVLA.  They then applied ‘Categorical Machine Learning Models’ (that crunch both category and variable data simultaneously) to give predictions about the likelihood of users changing car. 

Capturing data is a real issue for car dealerships. Many prospective customers for both new and used cars, start their online research journey elsewhere, often visiting the manufacturer’s site first or trawling online car supermarkets and AutoTrader before venturing to their local dealer sites and forecourts. 

These varied journeys to your dealership can make it difficult to build trusting and lasting relationships with your salespeople before the sale itself. But once they have decided to buy, that is surely the moment that data gathering and analysis can play a key role. 

Here are 5 steps to consider when building your AI-driven strategies for boosting customer retention and sales: 

  1. Use the sales handover as an opportunity to gather more details about how they arrive at the decision to buy from you, determine likely trade-in timing for the new vehicle and possibly other cars held by the family and; most importantly log whether they are fully satisfied with the car, service and finance package. 

 

2. Use this data to time communications with them with product and service updates secured. It is this data that may become the lifeblood of an AI project going forward. AI gives you an opportunity to time relevant communication for much higher response levels.

 

3. Make sure one of those data feeds for your CRM system is the deadline for PCP/PCH contract to end. Link to any information gleaned at handover or from previous purchases which indicates a propensity to switch earlier. Many new car buyers now aim to move cars even before their PCP have reached their maturity date. And some customers do this habitually.

4. They may even be contemplating changing brands, buying the car you’ve just sold them at the end of the current PCP period or trading down to an approved used vehicle, try to establish ways of gleaning this intelligence during interactions associated with that vital first service? Feed that data into the AI model as well and tune loyalty-linked communication accordingly.

5. If the business problem that you want to tackle with AI is improving customer retention, it’s simply about making it easier for customers to provide feedback which can be collected and analysed in an automated fashion to generate a ‘highest risk of switching soon’ customer list which can be given to a specialist customer retention team to act on.

Today there is a great deal of disruption in buying behaviour created by the uncertainty of Brexit and the simultaneous rumblings of electrification-inspired model refreshes following the fall out of ‘dieselgate’.

So, 2019 could not be a better year to develop an AI initiative designed to get closer to your customers and help them navigate buying decisions which just got a whole lot more complicated. 

 

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