Too much segmentation is as bad as too little
In an age of big data analytics, real customer intelligence depends on having manageable datasets to analyse, rather than too much irrelevant information that may drown you.
According to McKinsey’s “Unlocking the power of data in sales” report from December 2016, “more than 1,000 sales organizations around the world, we found that 53 per cent of those that are “high performing” rate themselves as effective users of analytics”.
With that in mind, we wanted to explore the complexity of segmentation and why too much of it can cost your business money. Cleaning and reformating data is a major first step when it comes to properly segmenting data sets, yet nearly 40% of 200 B2C and B2B companies surveyed by Allocadia claim they consider the process challenging.
Complex yes, but jumbling the wrong data together or putting it into too many categories can result in embarrassing errors such as; targeting the incorrect audiences for campaigns or sending the wrong email to prospective clients. Losing these opportunities is losing revenue.
Understandably, time is precious. CRM managers have a lot on their plates and need tools to help them be more efficient in how they analyse data. Experienced customisation requires a high degree of condensing multi-channel sources of data into fewer groups.
Segmenting your customers based on unsold inventory
When it comes to retail and consumer-facing enterprises something as simple as segmenting your customers based on unsold inventory can make a huge impact. Unsold inventory has surprising potential if advertised the right way, especially when using segmentation to find an audience for unsold stock that may not have been there before.
Dynamic search ads are an upsell tool for retargeting past customers, by promoting products previously viewed. According to travel platform Sojern, after partnering with Fairmont hotels and using Facebook’s dynamic ad offering in their advertising, they saw a 20% increase in revenue.
Segment for you
For online businesses, another way to simplify your segmentation is to utilise tools that target audiences based on their likelihood to become a conversion. Weeding out the leads from the bots and far away visitors can set a course towards attracting the right audience. Prioritisation should be personal to the company’s goals, segmentation becomes overly complex when data strategies are too broad.
Overall, as big data becomes commonplace in the business ecosystem, segmentation is a relevant tool needed to make sense of it all.