User Segmentation for Products

In this day and age of personalised marketing, how do companies reach out to the right audience and more importantly, who should be the target audience?

As a product manager, building a B2C product (in any industry, really!), the first question you will inevitably ask is :

Why should I segment my audience? I’m building a product for everyone!

→ Customised content is important : All customers/users cannot have the same desires, habits, likes or dislikes

→ Intuition is not good enough : Without segmentation, product development is just a matter of guesswork and nobody can be sure that a recent spike in activities is due to widespread adoption or recurring users

→ User retention is as critical as acquisition : It is crucial to know your users and build communication with them, taking into account their needs, benefits, and priorities

Still not convinced ? Let’s talk numbers :

A segmented, personalized push notification gets 800% more opens, according to data presented by Econsultancy

Segmented and targeted emails generate 58 percent of all revenue, according to the Direct Marketing Association

Facebook ads that target a custom audience based on purchase behavior and browsing history generate conversion rates that are 3.87 times higher, according to data presented by MarketingLand

Now that we understand why it’s a process worth investing time in, let’s cover the most common types of segmentation :

Geographic Segmentation :

Geographic segmentation calls for driving the market into different geographical units such as nations, states, regions, counties, cities, or neighborhoods. Markets can be considered by country or region, by size of city or town, postcode, or by population density such as urban, suburban, or rural.

Geographic Segmentation

Here are some examples on how products are geographically segmented based on these parameters :

a. The recent best example for location based geographical segmentation is Cadbury’s new ad in India, which is in the form of a video, starring a famous actor, who promotes a local store (it could be Kirana, footwear and electronics) by directly naming the store. The Ad uses AI to detect the current location of the ad viewer and accordingly promote a store in the nearest vicinity

b. Big online retailers like Myntra, Amazon, H&M, etc. change their promotional banners to winter-wear and summer-wear based on the season during which customers visit their website

c. From an advertising point of view it’s also important to consider local culture. A recent example of this is Toyota’s TV adverts for its new car the Camry.

Toyota’s TV Adverts

d. There’s a lot of support for language based segmentation— for example, Google Ads says it offers language targeting, which lets you target your ads to potential customers who use Google products and third-party websites based on the languages those customers understand

e. Big builders have real estate hoardings all around urban cities as compared to rural areas

Demographic Segmentation :

Demographic Segmentation

Some examples of demographic segmentation are :

1. While advertising apps like Instagram, Tiktok etc. marketers may use age based segmentation, eg : millennials may spend most of their time on Instagram and Facebook, while seniors prefer emails , newspapers for their information
2. When marketing items like diapers and cereals, organizations typically create advertisements that appeal to the traditional young nuclear family structure — father, mother, and children (marital status based segmentation)

Psychographic Segmentation :

Psychographic Segmentation

Some examples of Psychographic Segmentation are :

1. Premium branded companies like TAG Heuer, Omega, Longines, Rado, Tissot, Balmain, Gucci and other similar brands have positioned themselves in the Upper(Top & Bottom) Social Status segment
2. Discount stores like Big Bazaar and D-Mart target middle-class budget savvy consumers who intend to save money at every given place and time
3. Health brands advertise products such as olive oil, protein shakes, gluten free snacks to motivated people with a healthy lifestyle. This is an example of a cross between attitudinal and lifestyle segmentation

Behavioural Segmentation :

Some examples for behavioural segmentation are :

1. Black Friday, Big Billion Day are examples of occasion based segmentation where audience is targeted based on a universal holiday or occasion
2. Myntra provides a specific discount on customer anniversaries(eg : 5 years with myntra). This is an example of loyalty based segmentation
3. Users attempting to purchase a shampoo on the basis of benefits provided, eg: volumising , shining, enriching, etc. is an example of behaviour influenced by benefits sought
4. Office goers will be heavily dependant on commute apps(eg: Uber) in order to travel to work everyday. This is an example of usage based segmentation

Technographic Segmentation :

This segmentation is based on the customer’s preferred technology choice : eg : smartphones, softwares, operating systems, desktops, etc. Business to consumer marketing can also use technographic segmentation to target consumers according to their social media use.

What should I do once I segment users based on the above factors?

In product development, segmentation can provide product managers with critical insights into how users are interacting with their products. The following analysis can be done using the segmentation done above :

Step 1 : Make user profiles based on segmentation

Consider that the product manager is building an online marketplace where users can purchase products based on their interests -

Step 2 : Define Conversion Goals

From the above profiles, define the intent and purchase journeys of the users. For instance :

• Did they land on the product from a targeted email or push notification and complete the purchase journey
• Are they organic users who frequently interact with the product and make purchases

Step 3 : Identify any negative behaviours

• Has Greta stopped using the product suddenly if she has been inactive for <x> days?
• Does Christie only add items to the wishlist and never make any purchases?
• Have users like Drew abandoned the cart multiple times or dropped off at a particular step in the purchase journey?

Step 4 : Track metrics from a business standpoint

• No. of DAUs , MAUs
• What is the average customer LTV (lifetime value) ? Eg. : Customers like Greta would have a high LTV since they make periodic purchases on the marketplace
• What are retention and churn rates?
• What is the distribution of customers across user stages? Eg : Christie will be a first time user who would require nudges or incentives to make their purchases, Drew is a semi frequent buyer who could make purchases based on targeted advertisements and Greta is already under the motivated buyers segment

Last but not the least, the product team has to keep updating the metrics as well as the user segmentation based on analysis made from the above steps.

Happy segmentation!