Segmentation on user action

Most segmentation strategies focus on things like gender, geographic location, race, weekend vs. weekday traffic and the like. However, I have found that segmenting by user action is far more effective at driving conversion.

Let’s take a hypothetical that an e-commerce site has a wish list feature. Customers can put items on the wish list for purchase later. Let’s say a customer adds an item to the wish list. Now what does this tell us? It tells us the user is likely to return and since most wish list functions require registration we now have the personal info of this user. That means we can send them a customized and highly targeted email campaign or have the wish list product info dropped into a cookie so when they return a modal pops reminding them of the product.

Here’s another hypothetical: consider a web site with 3 levels for a service: novice, intermediate and pro. Let’s say the pro version has the most profit margin and that’s what you want to focus on. You could watch for a specific path in web traffic that indicates the user is a highly qualified prospect. For instance, if the user is a new user (has not visited the site before) and the pro product page is the 2nd or 3rd page visited by that user. That’s an indicator that this person is qualified, the site can then be optimized to convert that visitor to sale.

When your audience is telling you what they want with their actions, listen.

You can’t program creativity

Everyone’s talking about programmatic and real time bidding (RTB) advertising. In case you don’t know these terms programmatic and RTB is a robotic way to control and optimize ad spend that is highly targeted. When you start to load a web page your browser details and your cookie details are sent to a market place and ad impressions are purchased on a visitor by visitor basis. This is all done in 100 milliseconds.

Here’s an example: Bob likes sports, he visits ESPN frequently and his last Amazon purchase was a football. This information is stored in Bob’s cookies. Bob uses Safari as his browser. Safari users tend to be more techy and have more disposable income. A sports retailer has noticed that their mobile app has the most downloads between 6pm and 10pm on Tuesdays. The retailer would like to optimize their ad spend to generate the most mobile app downloads. So, Tuesday nights a programmatic campaign targets sports loving, Safari browser using people who made a sports purchase in the last 30 days.

Sounds spooky? Welcome to the modern world of digital marketing.

But a recent study showed that content marketing drives three times more leads than buying a SEM campaign. Why is this? Probably due to advertising overload. On the web we have become inured to ads. I have been on Facebook for 8 years. They know a lot about me. And yet I think I’ve clicked a Facebook ad once, maybe twice. And since it’s estimated that 35% of all adds are now served by programmatic systems it’s guaranteed that I have been exposed to the most targeted of ads thousands of times. But I don’t click. I’m sure graphic designers and marketers spent untold hours trying to make the most compelling display and text ads, but the pure fact that they are ads makes them entirely forgettable. Ironic, no?

But if a product or service had a compelling video or a blog post I would read, watch and maybe even click. If the content showed some creativity and thought I might click. If this content went out of it’s way to NOT sound like marketing or just a page to boost SEO results I might click. Even in this age of big data and software eating our jobs and driverless cars we crave humanity in marketing. 

Mobile strategy

A client asked for some help fleshing out their mobile strategy and in my research I found some interesting statistics and cautionary tales I’d like to share.

KPIs: if you’re selling something through a mobile eCommerce store, orders and revenue are clearly the metrics of choice. If you’re looking to collect user data, successful completion of the form is your goal. But for advertising campaigns, it’s a little trickier. The standard metric is click through rates (CTR) meaning, of those users who saw the ad, what percentage clicked it? Well, guess what? It’s estimated that 50% of mobile ad clicks are accidental. I know that seems like a lot until you think about it. Small screens and big fingers and no physical object defined to tap are perfect for accidental tapping. Then there’s the baby sitter factor. Since an iPad or iPhone is now a common plaything for toddlers and children of all ages, how many of them are stabbing their little fingers onto things they don’t even understand? Better mobile ad metrics, if you don’t have a clear cut sale or form registration to rely on, would be time on site and bounce rate. You also might want to intentionally build in a second step to your mobile landing page so step 1 is clicking the ad, step 2 is hitting the landing page where the value proposition is reinforced, step 3 is tapping through to the meat of the content and step 3 is your success metric for that ad that was seen in step 1.

Platform segmenting: Android and iOS users are not the same. Not even close. You need to break them out and figure out what works for each audience. There are 18% more users aged 18 to 24 on iOS devices. 39% of Android users make less than $50,000/year vs. 23% for iOS users. iOS users are 35% more likely than Android users to engage in m-commerce. iOS users engage in all activity more on their devices vs Android from the banal like checking weather to the more sophisticated tasks like mobile banking.

Browser segmenting: Safari market share is dropping while Chrome’s is rising and Android browser usage has remained steady in the last year. No other browsers matter in mobile. This infers that iOS users are switching to Chrome. Now who would do that? Safari works fine. The younger, techy and likely high earners is who. I bet if you took a sample of users on Chrome and iOS you’d find an audience much more willing and able to complete a task on a smartphone.

Location segmenting: location matters, yes, but in densely populated areas it matters less. First you want to target urban users because they have the data networks to make mobile a pleasant experience and a handful of urban areas control a huge amount of GDP

However, there’s a lot of demographic variety. Imagine if you will a Google exec hailing a cab on 14th Street in Manhattan. To the location servers the cabbie behind the wheel and the Google exec in the back seat look like the same prospect, but clearly, they are very different in terms of comfort with technology and earnings. However, if you then took all the people in that high earning zip code, targeted just iOS users and users on Chrome you would stand a much greater chance of getting to that Google exec who is your target audience.