In 1956, Wendell R. Smith revolutionized marketing by introducing his theory of segmentation. At the time, most marketers focused on making their products more appealing than their competitors. Smith argued that marketers could make more money by dividing customers into segments, then adjusting their marketing to these classifications. The use of segmentation today is seeing pressure to move to a more personalized marketing strategy. It appears that the value of segmentation has decreased in the digital era with technology enabling one-to-one marketing.
If the approach to segmentation is digitized, the potential to combine traditional and modern techniques expands the targeting capabilities of marketers. Augmented by artificial intelligence, machine learning, and other marketing technologies, segmentation actually evolves beyond its traditional uses.
Segmentation is still essential to the segment of one
In the past, organizations had to place individuals into broad customer categories. They didn’t have the data available to differentiate between each unique customer.
Segmentation that accommodates the segment of one retains the capacity to increase from a few segments to several million segments using advanced data analytics. This allows companies to keep existing segmentation standards, such as recency while achieving a higher level of individualization. Personalisation from that foundation increases customer scope. Marketing systems gather customer data, identities specific segments, and creates campaigns aimed at these customer segments. Automating segmentation cuts lead times for campaigns from weeks to hours, capitalizing on immediate trends and evolving to future consumer needs.
Businesses choosing to augment their existing models can apply omnichannel solutions with machine learning capabilities, enabling analysis of time-series data to predict customer need, and detect shifts in demand. This generates unique insights that allow companies to optimize their segmentation models.
Discover dynamic segmentation
A major criticism of the segmentation model is that it does not enable companies to adjust to the changing climate of consumer demand. Creating a dynamic segmentation model utilizing intelligent Cloud technology can automate the formation of segments. This builds complete, 360-degree customer profiles with transactional and behavioral data. It allows marketers to track customers’ buying journey throughout the buying process and utilize this information for future campaigns with machine learning. Combining segmentation with one-to-one marketing strategies addresses fluctuating customer attitudes to buying.
Rather than declaring the segmentation model obsolete, augmenting segmentation with digital innovations provides marketers more scope. We should leverage new technologies to offer insights into our modern buyers while making marketing campaigns simpler to execute and measure. Segmentation is as essential to marketing now as it was in 1956.
For more digital marketing strategies, see How To Use Geo-Targeting In Digital Marketing: 6 Tips.