Choices are good, but too many of them can kill the excitement. The same is true for the telecom operators sending hundreds of irrelevant offers to their subscribers only to push them away and possibly to another service provider. Unlike their webscale counterparts, Telcos were a little late to the game of personalisation.
Personalisation can only be achieved when you have a complete understanding of each of your subscribers and send them relevant offers or plans. Telcos switched from mass marketing to break subscribers into broad segments based on certain parameters. That seemed to work for some time. But as the subscribers evolved into digital-first customers, the broad segmentation is no more useful. A survey found that 91% of consumers say they are more likely to shop with brands that provide offers and recommendations that are relevant to them.
Micro-Segmentation: key to personalization
Micro-segmentation is a way to divide broad customer segments into smaller, more homogenous small segments with similar behavioural and psychographic traits. Micro-segmentation has evolved over time with solutions that support precision marketing techniques where the segment size could be the “Segment of one” or “n=1”, where you target every individual with an offer tailored to their needs.
Each micro-segment has an intent, or an objective based on the campaign manager’s need, and it varies depending upon the micro-segment’s dominant behaviour. Let’s understand with an example here. Say intent for Segment A could be ‘upsell of packs’ as they are already on a pack, and the intent for segment B could be to reduce churn as the segment show low engagement and have a high churn score.
Micro-segmentation helps the marketer understand the subscriber behaviour even before targeting. The marketer understands their needs and addresses it directly basis the segment intent rather than the ‘one size fits all’ approach. This improves the campaign performance, resulting in higher take rates and better ROI.
Slice and dice customer data for micro-segmentation
Every marketer understands the importance of creating a micro-segment for personalised campaigns. But, breaking down a large segment base into small homogenous micro-segments is not easy. You need to obtain in-depth, highly indexing attributes for each base segment. These highly indexing variables can be identified through segment analytics. It allows for a more holistic understanding of each base segment and identifies the potential characteristics to create micro-segments.
Slice and dice help analyse the broader audience group by breaking them into micro-segments. To arrive at the micro-segments, individual subscribers are clustered using key attributes that express the homogenous behaviour. It gives a holistic view by distinguishing the customer base into different groups to identify the good, average, and best performing segments. Once the user identifies a particular segment, each segment can further be drilled down using defined attributes to arrive at an intent or objective to launch campaigns for the microsegment.
Once the micro-segment and the intent for the campaign are identified, pilot campaigns are executed to measure the micro-segment and offer efficacy. The best micro-segments, along with the best performing offers, are broad-based to evaluate the campaigns and KPI’s basis the campaign intent. Here are some of the attributes that can be used to create micro-segments:
- Geographic
- Demographic
- Psychographic
- Behavioural
- Product based
- Benefit based
- Volume/usage based
How mViva can help micro-segment subscribers for better targeting and campaign performance
Micro-segmentation is an important capability for any campaign management solution to allow marketers to plan and execute highly targeted campaigns. Pelatro’s mViva, an advanced marketing platform, uses two different methodologies to microsegment the larger segments.
1. Slice and Dice:
Users can select KPIs/Attributes for micro-segmentation, perform the base analysis on the platform, run pilot campaigns, and extend the best campaigns to micro-segments.
2. Segment Shatter:
Automatic identification of segments or clusters based on AI-ML technologies, Hierarchical Clustering and Neural Networks.
Want to know more about Micro-Segmentation and how we are helping our customers with better targeting, contact us.
