What if you could determine the advertising cost of every single new customer acquired from advertising down to each click, each ad, each effort, each medium, each demographic? You could likely make some huge improvements, do more of what was working, and scale your business (or profit) dramatically. That’s precisely what you can do with advertising data science.
Most companies are advertising in multiple different ways (different ads, events, content, etc.) dispersed to a myriad of different peoples (demographics, geographies, etc.) at different times. Some companies know average customer acquisition costs for a particular medium (all Google or billboards for example). Very, very few companies know how the cost by hour, demographic, medium, billboard, etc.
Determining Customer Acquisition Costs (CAC) through data science is the answer. Breakdown the cost by every conceivable metric until you can point to a customer and know how much it costs to acquire them through advertising and quantify how they fall off in the sales funnel starting with your ad and every touch point until revenue.
You'll likely find 70 to 80% isn't working. Further some small changes to the customer experience yields a giant improvement in your sales funnel. We’ve never seen a client spend even 30% of their money well (that means 70% is wasted on people who can’t or won’t buy).
“What about efforts I can’t measure?” Did your customer come from digital ads? A billboard? SEO? Email campaign? You name it. You can measure it. We’ll do follow on posts describing how to quantify numerous aspects. Follow to see more.