The following excerpt is from franchise expert Mark Siebert’s book The Multiplier Model. Buy it now.
When it comes to franchise success, continually striving for improvement is key. In the marketing world, we call these A/B tests.
In an A/B test, the goal is to isolate two variables to determine which one works better. This is imperative for decision-making and business growth.
Here’s a quick example
Let’s assume you’re running a pay-per-click (PPC) ad for a home-service business, and you want to know whether an ad that touts same-day service is more effective than one offering a money-back guarantee.
By running both ads and measuring the results against similar audiences, you could see which message resonates better.
Now take that example and tweak it
Then you could try two more ads with two completely different messages and measure their results against the winner of the first test or go head-to-head in a real-time matchup.
Doing this can significantly improve how well your message resonates with your customers.
Do this again and again, and ultimately you will have statistical evidence as to which message (or messages) work best to attract your targeted buyer.
Refine your A/B tests even more
There are all kinds of variants and refinements you can try. Perhaps B won your first A/B test, and now you need to decide between B and C (this process of incrementally improving your messaging can — and should — go on virtually forever).
If you’re testing PPC ads, you could send the respondents to different landing pages, creating two sets of A/B tests with your messaging — one that measures the drawing power of the initial message and one that measures the power of the message on the landing page. Now your testing process begins to look like a decision tree.
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Test across different media types
What we are talking about here is creating a system that you have tested, measured and refined until each element of the system works.
Now imagine that the system you’ve built for your advertising message can be extended beyond just the message to the media that carries it. Each form of media can produce different leads for you, at a different cost per lead. And each of those leads will have a different value to you in terms of cost per sale. So you need to measure these variables during your testing process as well.
If you can do that across the entire marketing spectrum, you can refine your media mix and your advertising budget along with your message. This will allow you to optimize your marketing and create a true system for the entire marketing process.
Keep in mind, though, that when you measure this system against your financial performance, you should only keep it if it generates revenue for you at a rate that allows you to provide your service (or your product) profitably.
If your marketing costs are so high that it becomes impossible for you to turn a profit, you need to go back to the drawing board and find something (different marketing, hopefully, but perhaps different products or services) that will allow you to make money.
Go beyond the marketing example
The example above is how successful marketing systems are created.
But these systems are not just limited to marketing: In the best businesses, they are incorporated in almost every repetitive function of business operations — from site selection and build-out to hiring and training to purchasing and pricing to production and delivery.
Related: The 9 Provisions Every Franchise Agreement Needs to Have — and What They Mean
Get started with The Multiplier Model
Going from small business to successful startup to scalable growth takes more than just good luck. It takes a system. Over the last 34 years, franchising consultant and growth expert Mark Siebert has been sought out by more than 70,000 executives looking to expand their companies. Out of those 70,000, only 5,000 had the right systems in place to go from successful to scalable. In The Multiplier Model, Siebert discusses the factors that determine if an entrepreneur is ready to scale their venture — and the best ways to get started. Read more.
