Written by: Kiesha King-Brown, Senior Level Executive Contributor
Executive Contributors at Brainz Magazine are handpicked and invited to contribute because of their knowledge and valuable insight within their area of expertise.
If you’re in Entrepreneurship
If you’re in Retail...
If you’re in Marketing…
You’ve adjusted to a world of constant change, and you don’t mind leading through change.
But that doesn’t mean you can’t maximize effectiveness of your leadership, strategy, and bottom line by leveraging the ability to better predict customer behavior. AI gives marketers and businesses the best understanding of how customers choose to make decisions about, utilize, and shift between different products and services. It helps identify preferences and attitudes that influence buying behavior.
AI helps marketers and businesses understand the needs of customers and the value to customers… from the perspective of customers.
Because AI provides these understandings based on data at scale, it enables prediction of future behavior. These predictions can be done through segmentation and/or predictive analysis.
Segmentation is a more familiar concept to most. It’s simply separating customers or markets into smaller groups based on specific categories.
It used to be that groups were primarily demographic based on age, gender, education, income, marital status, race, occupation, family size. Demographic segmentation is about the “who”. It’s surface-level segmentation. For instance, it might define groups who would be more likely to purchase clothing from a luxury brand vs. from a value retail player based on age, education, income, occupation, family size, etc.
Better segmentation is based on buying behavior. This is “the how”. This behavior can be inclusive of spending habits, purchasing habits, browsing habits, interactions with a business or brand, interactions with a business’ competition, or acts of loyalty to the brand. And it’s not an action, it’s an identified frequency of actions.
A type of segmentation not often discussed but relevant in some industries and becoming more relevant is technographic segmentation. This is a group of customers relative to the role technology plays in their lives. An example could be early adopters when a business is marketing a new tech product or personalizing messaging and offers based on the device used to access a brand’s site.
Knowing whether a customer typically uses their mobile device allows a business to know to reach them there vs. a customer who may typically engage using their desktop computer. This information can also benefit marketing campaigns by customizing messaging to a customer’s specific type of technology. But this type of segmentation is best used in combination with behavioral segmentation.
Market or customer segmentation provides more effective marketing, better cost efficiency, increased customer retention and brand differentiation.
Now let’s take it to the next level with predictive analytics which is powered by the machine learning (ML) function of AI.
I don’t think there’s any argument that increasingly more challenging economic conditions, ultimate change, also increases the need for a differentiated competitive advantage… more than just segmentation. So, let’s focus on going from:
Leading through change
Learning from change
To taking some of the guesswork out of change.
Say ‘hello’ to the potential of infinite data that isn’t being sifted through manually at the rate of people, but now at two-thirds the speed of light! Now we can find zillions of once undetected “needle in a haystack” type patterns, insights, and anomalies to create data-driven marketing and business strategies relative to predicted next customer actions. Instead of leading through change…you can step up your game, your presence in your industry, and be the leader of change…
On behalf of...
The customer.
The bottom line.
And future growth.
Kiesha King-Brown, Senior Level Executive Contributor Brainz Magazine
Kiesha King-Brown is a business savvy, customer centric tech enthusiast. She is EVP of AI Strategy for Enterprise Retail/eCommerce at ADMD Solutions and Chief Operations Officer at iDo Systems.
Kiesha partners to maximize the effectiveness of branding, marketing, and strategy with the power of AI. She also helps Start-ups and businesses with intuitive go-to-market strategies and the only smart platform, Pillar Five, that functions like a Smart GPS to get businesses from Seed stage through maturity successfully and supports a technology-based ecosystem.
Kiesha has a Bachelor’s in Marketing, an MBA in Management, is a member of the AI Academy for Marketers and a Certified Executive Coach. Kiesha has held Sr. Leadership positions in Fortune 200 Retail Companies serving up to the Territory Level and working on company level strategy. She has also helped small businesses improve strategy and profit in own her consulting business.
