Income targeting is a powerful segmentation lever offered by platforms like Google and Facebook across the globe. The effectiveness of this feature is usually limited to developed countries where these engines are able to define a high share of its user base’s income.
In other parts of the world, however, search engines struggle to understand which households have what income. For example, in some African countries as much as 95% of sessions come from an unknown income.
What are sellers of premium products to do when explicit income targeting isn’t offered in a local market?
Option #1: Find 3rd Party Publishers of Income Data
In many countries the government will publish the equivalent of census data with income by region. This is a fantastic place to start; By simply marrying Google’s defined regions to census data on income levels a marketer is able to gain valuable insights into the income makeup of a region. Naturally, users with higher income should be able to afford higher priced goods.
Option #2: Identify Regional Industries
When government or 3rd party income data is not available understanding regional
industry can go a long way. Often, industrial sectors influence the wealth of a particular region. For example, areas with heavy farming and agriculture tend to have many low-wage manual workers, whilst manufacturing regions tend to have slightly higher incomes. Cities will generally be higher still due to the high prevalence of service industries, with regions characterized by banking and technology will be the highest.
Option #3: Look to Languages
The language people use to search can be telling of education level. Education, in turn, often correlates well with income. What does it say when a user searches in English when the primary regional language is Swahili? Zulu? Kosa? Arabic? Hindi? By segmenting uniquely on default browser language and search query language we get powerful access to multi-lingual, well-educated customers, and potentially high-earning users.
Option #4: Mobile Device Model
It is well established (see my previous post on "device as demographics") that the device which a user accesses your site on correlates well with income level. iPhone users tend to be more affluent than Android users. Segmenting further, iPhone 7 users will be more affluent than iPhone 4 users and Samsung Galaxy 8 users will tend to be more technologically savvy and wealthy than Samsung Galaxy 6 users.
Option #5: Don’t Forget About Desktop
In many markets, millions of users are coming online for the first time using a mobile device. Perhaps affording their first cell phone, these users may lack the savviness or payment inputs required for checkout in 2017. While smaller in aggregate numbers, owners of laptops represent an important demographic because in many emerging markets owning a laptop signals that the potential customer has a job that requires a computer or is a top earner and has been online for some time.
Option #6: Mine the Search Query Report
Hidden in the search query report is the grammatical nuance to segment users efficiently. It is straightforward to segment on users using discount terms such as ‘cheap’, ‘free’, ‘low-price’, ‘sale’, and ‘special offer.’ Experienced managers can take this a step further. When common words are misspelled or spelled phonetically it may be indicative of a less educated user or users attempting to search using a keyboard that does not match their native tongue. This can be seen in India where Hindi speakers rely on western keyboards and paradigms.
Option #7: Look at Regional ARPU and Basket Mix
First party data is often best. If a business has a standard product mix across regions they can observe different order mixes across cities and even neighborhoods. In Africa there can be vast disparities in purchasing power across regions. Whether users order premium products or base products can inform an array of marketing decisions from medium (billboards vs mobile banners) to message (premium vs sale) and activation strategy (offline vs online).
Option #8: Understand Product and Business Affinities
Sometimes, other products users are interested in can be indicative of a user’s ability to afford your product. Does a potential customer ‘like’ an import brand of beer or the low-priced domestic offering? Have they shown interest in upmarket hotel brands or budget youth hostels? Do they drive a two-wheel scooter or a four-wheel SUV? When in doubt, look to a person’s past purchasing intent as in indication of future purchasing ability.
Good marketers leverage the rich data available in advertising platforms. Great marketers supplement this with external data to drive insights where the competition isn’t. In less mature markets, advertisers need to be particularly crafty to introduce data so they can effectively segment traffic.