Muldowney: How auto service providers can reach more customers by spending smarter

These days, automotive services marketers are looking at their budgets more carefully than ever, trying to determine the most cost-efficient ways to attract customers and keep repeat business coming. That often means choosing the best communication channels.

But with more options than ever to consider, what's the smartest investment they can make?

Radio, TV, billboards, print ads, direct mail or digital advertising, including everything from paid search to subscription services to social media like Facebook and Twitter — that's a lot of choices and comparisons to make.

Perhaps most important question is how effectively will they all work together?

While businesses have grown increasingly sophisticated at measuring the success of individual channels, using attribution to link media channels and customer touch points with return on investment, marketers now also need to know how all these marketing activities combine to impact sales. For many retailers, faced with these complex marketing decisions, channels and data, the next step has been to maximize their return on investment by adopting Marketing Mix Modeling (MMM).

MMM allows automotive service marketers to really wrap their arms around the whole process of knowing what's working best and how to spend smarter in the future. Using historical data, this weekly, quarterly, annual or longer-term analysis gives businesses a comprehensive overview to guide their media planning decisions. Based on past marketing spend and sales, a marketing mix model can guide their future spending for maximum ROI.

As opposed to the idea of attribution identifying the real-time media touches before a customer buys and what channel gets credit, MMM takes an aerial view that factors in marketing, sales data, revenue, benchmark costs and outside factors, including economic conditions (such as COVID-19) and all kinds of market conditions and drivers.

All the data from the marketing "Mix" elements — product, price, place and promotion — including media, is analyzed to see how well they are working individually and how well they are working together. For a business with several different marketing channels, both online and brick-and-mortar presence, and diverse products and locations, things can get complicated really fast.

For example, let's say that an automotive service retailer wants to know how each of its media channels contributes to sales. And that retailer has collected sales data and media spend for each channel over the same time frame. Based on many different points in time, the brand can run a "multi-variate test" to analyze the data and predict how a change in media spend will affect the sales outcome. Seems straightforward, right?

In practice, all that tidy-sounding information can come at the business like a swirling mass of data that's not only confusing but seems to raise more questions than supply answers. And, while the old adage "garbage in, garbage out" still applies to subpar data collection and organization, done right, MMM is how brands can tame that data and find the answers by building statistical models that will predict their success — before they spend their money.

One of the first considerations is base sales: the number of sales that you can reasonably assume are just going to happen on their own.

Incremental sales volume is the target here, marketing through channels to guide the customers to the brand, whether for brand awareness or acquisition. All those channels have their own means of measurement to indicate success, finally linking up for total, measurable, incremental sales.

The goal is to capture the marketing history and align it to current sales. But there are plenty of other considerations along the way and blind spots to be revealed.

Let's say a multi-channel automotive service provider has had pretty good success with a weekly flyer, maybe it's a newspaper insert, and it traditionally claims a significant chunk of the marketing budget. But they don't really know what their other options are. Is the flyer as effective as they once believed? Should they move dollars into other marketing channels? They might try CRM (customer relationship marketing), leveraging customer data to do a targeted mailing that will be measurable while building up their customer knowledge.

Maybe they've also consistently run TV spots and know the total rating points but can't really correlate the impact to sales projections. Modeling can tell them that and whether that impact is degrading over time. Maybe they are over saturating their TV presence, wasting money for diminishing returns. Modeling can tell them the ROI sweet spot. At the same time, MMM may recommend diverting some of those dollars to radio because it has revealed the efficiency of their occasional radio spots.

Maybe the brand would also discover that despite 40% of their targeted customer base being women, their media spend doesn't align enough with that important group, prompting a shift within the channel or a jump to another.

Or perhaps the MMM reveals that a younger population has grown more important — and responsive — than the brand realized and prompts them to double down on social channels that skew to this group. This modeling gives marketing decision-makers the dials to fine-tune their marketing campaigns for the best signal, allocating spend in percentages that have been shown to increase profitable return.

At its core, MMM helps automotive services providers eliminate guesswork and gain deeper insight into what's working and what's not.

Backed by data science that quantifies their decisions — and lets them defend their budget — these businesses gain high-level analysis across all their media spend, giving them the long-term strategic planning insights they need for smarter spending.

Rick Muldowney is the chief analytics officer for digm, the marketing agency that combines complex data analysis and marketing technology to create a holistic customer view with insights that drive businesses forward.