It’s the end of a long, tough workday in winter and an email arrives from a spa you’ve gone to a few times. It offers you a discount on services you’ve had in the past, and you think yes, this is just what I need. You pick up the phone and book an appointment.
Delivering the right message, to the right customer, at the right time, is what marketers strive for. Big Data and advances in analytics tools, are making these types of personalized offerings possible — revolutionizing customer profiling and allowing for the next level of consumer connection and one-to-one marketing.
The key is micro-targeting. This uses new statistical methodologies and computer algorithms to sift through the mountains of data captured from customers to identify the micro-clusters and behaviour triggers that drive targeting and marketing activity.
Your most loyal customers can be product or brand advocates, and their social media activity can become your tool to target other customers.
Done right, micro-targeted messages slip past consumers’ ‘mass mailing radar’ to create a positive view of an offer or product without resorting to overt promotion. At the same time, micro-targeting provides customers with the personalized attention and service they crave.
Making micro-targeting work
We looked at the micro-targeting revolution in our recent report, Customer-focused growth: Rising expectations and emerging opportunities. If you’re considering how to use micro-targeting to reach your customers more effectively and persuasively, here are some factors to keep in mind:
It’s about data variety as well as volume
Effective micro-targeting is most effective when we have lots of data, and not just the point-of-sale, customer relationship management (CRM) or enterprise resource planning (ERP) information that’s commonly captured. Companies need to identify new sources that can provide them with unique information about their customers, the kind of information that can be harnessed to deliver timely, targeted messages that surprise and delight the recipient (like a great spa-package deal).
These sources can include the following:
Companies need to identify new sources of data that provide them with unique information about their customers, information that can be harnessed to build custom prediction algorithms that are unique to their business and give them an edge over competitors when marketing to their customers.
Find and target key influencers
Who influences the people who buy your products and services? Finding those people, organizations and media channels and creating a targeted strategy to get your message out through them can have a powerful impact on your marketing efforts.
In many cases, you can find these influencers in the data: your most loyal customers can be product or brand advocates, and their social media activity can become your tool to target other customers. Advanced analytics methods can uncover patterns and trends that can point you toward the individuals and organizations that regularly engage with your customers.
Companies can also identify the key influencers in their market such as bloggers and other social media personalities to traditional journalists and industry commentators. Those with the biggest following can potentially be your worst nightmare; they can also be a big asset to your customer engagement strategy if properly approached.
Start small. Test. Learn. Repeat
Now that micro-targeting is actually feasible, it’s easy to get caught up in the excitement of making one-to-one marketing a reality. This is an emerging area, however, and companies should guard against trying to do too much too soon, including making a major investment.
Test the waters first:
These efforts will help improve your company’s ability to understand, integrate and analyze customer data before making a major push into micro-targeting. Many excellent tools are available to help companies pilot and determine the impact of their micro-targeting efforts.
Tom Peters is an Associate Partner in the Analytic and Forensic & Dispute Services practice of Deloitte in Toronto. He is an experienced professional and subject matter expert in the customer analytics and marketing sciences field and is a subject matter expert in the application of multivariate statistical methods for segmentation and consumer demand modelling.
Tom has spent the better part of the last 20 years working with clients in Canada, the United States, United Kingdom and Australia within a wide range of sectors including financial services, telecommunications, travel, QSR, agriculture, automotive, power utilities and technology.
