There’s been no shortage of persona talk over the years. Heck, every major brand probably has a persona developed of their typical customer. Marie the Millenial Mom, David the Dynamic Dad, Uncle Bob etc. Usually, there’s two or three key personas (the shopper, the buyer and the whale) and they all fall into a neatly refined box.
When we put search campaigns together, we tend to defer to the end user, the best persona – we want the person who’s going to use our product to demand it in their house/office/car/whatever. Makes sense right? They’re the ones supposedly making the purchase decisions. So we focus our bid strategies on these perceived personas, and eliminate those who don’t fit in.
Where the problem comes in is they’re not always the ones doing the searching, clicking the buttons or entering the credit card numbers. Enter sweet, delicious data. I’ll present a few examples below.
Targeting the opposite gender (or how I learned to stop worrying and sell purses to dudes)
Client: Luxury women’s accessories.
Case: Selling purses to dudes
What we suspected: Men don’t just buy purses around Christmas and Valentine’s Day. They buy them year round for birthdays, anniversaries and times they screw up and stay out too late playing high-stakes bingo.
Findings: The data in the chart below represents May-July – also known as not peak male purse buying season. We enabled demographic reporting in Google Analytics (also available in AdWords), and took a look at the data. What we found was males converted at A nearly 40% higher rate AND they spent 10% more per purchase. No time to price compare when you’re in the doghouse!
Action item: Think twice before you cut the other gender – let the data do the talking.
The richest are (almost) always the highest spenders
Client: Mid-level fashion retailer. It ain’t quite Givenchy, but it’s not Forever 21 either.
Tactic: Household income bidding (AdWords, Social)
What we think: No matter the brand or target, higher household income customers will spend more with a higher basket size, since they’re not price sensitive. That means by default, you should put in a +20% bid modifier for top 10%, +10% for 11-20%, -10% for 41-50% and -20% for lower 50%.
Findings: The hypotheses were wrong, wrong andddd wrong. The wealthiest members of this audience convert the worst, have the poorest return and don’t spend as much as others. For aspirational mid-market brands, their sweet spot tends to be 20 somethings who have a little bit of money. Our dear girl Millenial Martha perhaps. We would’ve been doing ourselves a disservice if we simply blanket bid more for high income households based on an assumption.
Action item: Add HHI targeting to your audiences to gather data BEFORE you make bid modifications
Challenging personas: the audience you target may not be the audience that responds
Client: Direct sales for wine (think Stella & Dot, only drunker)
Tactic: Demographic targeting – age (GDN, Social)
What we think: The primary target audience and most likely persona is a stay at home mom with teen or adult children. She’s bored at home, and looking for a way to get back to work. We should focus our efforts entirely on the 45-64 demographic.
Findings: You know where this is going. The hypothesis was wrong, minority audience performs better and has a roughly 40% higher conversion rate. Turns out young people like booze too.
Action item: Segment your social & GDN campaigns by age.
Take this data with a grain of salt – obviously these are hand picked examples where the contrarian bidding example worked out. But there’s a few clear action items here for everyone. If you ever have an opportunity to gather data as you develop your campaigns, TAKE IT. Enable household income targeting in search, turn on demographic reporting in GA and above all else, segment your campaigns like your life depends on it.