LGM Financial Services recently made history with the launch of its Recommendation Engine.
A digital self-service tool, the Recommendation Engine is designed to help consumers learn about specific F&I products that fit their requirements.
The tool works by asking the consumer a series of questions and then leveraging machine learning to deliver recommendations that are specifically tailored to them.
The tool’s introduction signifies a major change in the way F&I products can be presented to dealer customers and changes the dynamic between vehicle shopper and dealer representative.
To find out more, Autosphere.ca conducted an exclusive interview with Jeff Schulz, Executive Vice President, Marketing for LGM Financial Services.
Autosphere: Tell us a little about how the concept of the Recommendation Engine come about?
Jeff Schulz: It really came about as a result of what was happening in the industry. We saw that more and more consumers were going online and doing research about their vehicles.
We realized that there was very little in the early stages of research for consumers as it related to F&I products, such as protection and extended warranties.
Based on that we felt there was a great opportunity to engage them earlier in their journey because at that stage they are shopping for the type of vehicle, looking at options and figuring out monthly payments.
Therefore, it made sense to create a tool that would allow us to engage with consumers at this stage by asking them a few simple questions and providing information on the kinds of products they might want to consider.
The whole concept was not to deliver a hard sell but to just ask six or seven questions that you might do when you’re at the dealership actually figuring out how to pay for the vehicle, including the options and F&I products you want.
What to look out for
AS: Were there key things you were looking to address with the launch of this tool?
JS: We conducted a big research study and we asked a lot of consumers about the kind of vehicles they bought, what they considered and along with it, the F&I products they bought, and how they found these products.
We then asked different questions such as who provided a description of a particular F&I product and how likely the consumer was to purchase it.
What we found was that there were some really interesting correlations in how consumers answered those questions. Most of them said is they didn’t really have a high awareness of the products.
They might have heard about some of them, such as extended warranties, but had very little information about products such as loans or appearance protection. From that, we were able to look at the data and see that it was fairly predictive based on the answers received from the questions we asked.
We then took that data, and the survey and created a predictive model overlaid with our own experience in the industry on the kind of products people with different lifestyles were likely to consider. We put them together and created the Recommendation Engine tool.
AS: Was there anything else you discovered?
JS: With the tool, we realized that in the dealership, you can ask the consumer more questions such as ‘how do want to pay for this?’
And, ‘how and are you planning to finance it?’ ‘Are you planning to pay cash, finance or are you leasing? How long do you plan to keep the vehicle, how many miles/km do you plan to drive?’
We took the same kind of overall process and created something that would work really well in the dealership where you could get the consumer to fill out those questions or the salesperson could actually just complete those, and it’ll come up with a list of the products that are most likely to fit the customer’s needs with the terms they prefer.
Essentially then, we’ve got two levels, upfront and the customer journey, and then the dealership experience which is a little bit more involved and more specific in terms of recommendations.
A smart tool
AS: Anything you’d like to mention regarding the specific workings of the tool?
JS: With our Recommendation Engine, the built-in machine learning means that, as the volume of respondents increases, the tool is constantly refining itself and refining the searches, because it works based on what people have said and what they’ve done and what they click on.
For example, if they click on ‘more information’ about the different products, the tool will feed them that information. As a result, it’s constantly getting smarter every time, which we think is really interesting and kind of cool.
AS: What do you think resonates most with consumers when it comes to making decisions regarding the purchase of F&I products and how does a tool like this aid the process?
JS: What we really wanted to do was to create something where consumers didn’t feel they were under pressure to make a decision.
With the Recommendation Engine, they can look into something and the tool will come up with recommended products related to that search.
From that, they can get a sense of the coverages and products available, how much they are likely to cost on a monthly basis etc., and they can do that from the comfort of their own home.
They can then print off the result, take it to the dealership and say ‘this is what I’d like to consider with the vehicle I’m planning to purchase.’
AS: You’ve been working with OEMs to integrate the product into the car buying experience, can you tell us a little about that?
JS: We’ve been working with OEMs to integrate the Recommendation Engine into the actual online vehicle building process, so at the same time their spec’ing their vehicle, the consumer is answering questions about financing and leasing etc.
By working with our tool, these financing and lease questions allow F&I product recommendations based on the customer’s preference for purchasing cash, financing or leasing.
For example, if you are leasing, you might want to consider lease protection coverage, or if you’re financing, you may want to look at loan protection.
In essence, the tool allows the consumer to learn more about the F&I products they are likely to consider before they even set foot in the dealership.
AS: What are some of the benefits for dealers and sales staff in leveraging the capabilities of the Recommendation Engine?
JS: Much like on the consumer side, I think the same principles apply.
The tool allows dealership staff the ability to send the consumer a link via their phone, giving them the ability to answer questions about what they are interested in and make recommendations for F&I that are very personalized based on the consumer’s needs.
Again, it’s a more engaging way and a useful addition to the sales process, because it involves the consumer and allows them to talk about some of these things.
Essentially it enhances the traditional sales process and still allows the consultant at the dealership to provide more information once the consumer is there.
Another interesting development is that most consumers today want to start their vehicle purchase journey online and there is an increasing trend of more people who want to conduct the entire transaction online, though overall, I believe most people want a combination of both online and in-store experience.
Yet as we’re seeing these trends unfold, from an F&I perspective, having a tool like the Recommendation Engine will allow the consumer to be engaged earlier, answer the questions, figure out what they’d like, and be pre-disposed in making decisions regarding F&I products at an earlier stage in the sales process.
AS: How do you see the Recommendation Engine evolving as a key part of the F&I space?
JS: I think the F&I process is going to be very dynamic moving forward.
Because our Recommendation Engine has machine learning built into it, it can constantly evolve and fine-tune its recommendations. Dealers are going to be selling online and this can be a really effective tool to help the consumer figure out what’s going to work for them.
Over time, the tool has the ability to become smarter, making the process easier for the consumer and enhancing the sales experience with the dealer.
It will be one of those things that become almost seamless and it’ll be a great support to the dealership because the consumer is now pre-conditioned to think about F&I products, meaning it doesn’t have to be such a difficult sell for the dealer.
AS: Is there anything else you’d like to mention?
JS: Ultimately, our goal is really to create a better consumer experience and we think this is one of the really important ways in which to do that. We’re excited about the Recommendation Engine and have spent a lot of time and energy on it.
So far, we’re getting really good feedback from our dealers and the OEMs that are looking at it, so it’s exciting.
As we see the bricks and mortar aspect of the sales process become integrated with the online element, I feel we’ll be able to create a significantly better experience for our customers.