Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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How To Master Customer Retention Using Artificial Intelligence

By Nand Kishor |Email | Nov 18, 2017 | 11445 Views

Today's consumers are overwhelmed by a constant deluge of advertisements and promotions. They are tired of the noise and fatigued by all the product options. They increasingly desire the personalized attention they get from Amazon and Netflix from all the brands they interact with.

Of course, not every brand can be an Amazon, but companies are starting to recognize that they can no longer rely on traditional marketing strategies. They have to better understand their current customers and focus the majority of their marketing energy on retention, not acquisition.

Statistics show the advantages of customer retention. It is six times more cost-effective to retain a current customer than it is to acquire a new one. Existing customers are 50% more likely to try new products and spend 31% more money compared to new customers. And increasing customer retention rates by a mere 5% will increase profits by 25% to 95%. Still, despite this overwhelming evidence, only 18% of companies make retention a top initiative.

But there is hope. Advanced analytics delivered through artificial intelligence (AI) offers a new way for retailers to glean customer insights from their data. AI sharpens the four data lenses that can be used to provide vivid snapshots of each individual customer. These lenses are: demographics, psychographics, behavioral patterns and intent.

Demographics is inarguably the most important categorization tool for marketers. The further a marketer can separate customers into small segments -- a process called microsegmentation -- the better they can tighten their focus on them. Micro-marketing campaigns can appeal to customers' refined tastes, but in order for them to work, you must first know a customer's basic demographic information. Demographics allow marketers to create distinctions based on age, gender, geographic location, income, number of children and marital status.

Dollar General markets based on income, offering deals to the budget-conscious customer. McDonald's successfully targets by age category, marketing Happy Meals and toys to children, breakfast meals to older professionals and coffee to senior citizens who like to meet friends at the chain's restaurants. Proctor and Gamble, on the other hand, segments by gender and offers the "Secret" brand deodorant to women while marketing the Rogaine treatment for hair loss to men.

A complete understanding of customer demographics is vital to a successful marketing effort. Not every product will appeal to everyone. But if a business has a clear idea of the type of person who will most likely use its products or services, it can tailor its marketing accordingly.

Delving into how to customers think, and thus how they will react to marketing offers, the psychographic lens focuses on customers' personality types, opinions, attitudes and interests. Psychographic characteristics are not as visible as demographic ones. It takes more effort to discover these traits, but they are worth knowing because they let companies market the same product differently to different customers.

Companies can study opinion surveys to see customers' psychographic leanings, but people today are less likely to take a survey and more likely to openly share their thoughts on social media. Walmart excels at using social media technology to tap the power of psychographic-based marketing. The company predicts its customers' tastes based on their social media posts, shares and likes.

Behavioral Patterns  
Unlike demographic segmentation and psychographic segmentation, behavioral segmentation focuses less on who the consumer is and more on the consumer's distinct actions (i.e., purchases and returns, complaints, product reviews, etc.). These actions are governed by various factors like occasion, benefits sought, brand loyalty and purchase readiness.

Behavioral segmentation allows companies to market solely based on how a customer reacts to a specific product or past marketing campaign. With this historical viewpoint, companies can deliver successful marketing messages. They can also strengthen their customer retention efforts by focusing on customers who have demonstrated positive behavior toward their brands.

As an example, through analysis of transaction data, one of our clients found that most frozen dinner purchases were based on price, not brand or cuisine type. This retailer changed its display to include all economical dinners together, irrespective of cuisine or brand. The result was a significant lift in sales, as customers picked up more items to include variety in their dinners.

Intent segmentation tries to ascertain what customers are doing at the top of the marketing funnel. It's difficult to misunderstand customers at this stage because they are clearly signaling their intent. They are telling a company what they are looking for via referring search keywords, referring URL, a direct email message, a comment on a social media page or call to a customer service line.

Non-verbal behaviors also help determine level of intent. Creating a cart and abandoning it, for instance, clearly shows a purchase intent that requires a push to be completed. Similarly, someone who only looks at your homepage is indicating less intent to convert than someone who takes the time to read through multiple pages.

Intent-based segments are particularly useful when you have a diverse product line. Broad matching and grouping referral keywords to define these intent segments allows you to serve content specific to consumer intent/interest and reduce bounce while increasing leads and sales.

AI-Powered Analytics For Insightful And Timely Customer Data
These four data lenses provide great insight on consumers, but when viewed on their own, they won't shape the 360-degree perspective that companies need to fully understand in order to retain customers. When linked, these four lenses provide a clear, holistic view of every customer that allows companies to strengthen their retention efforts with timely, tailored marketing pitches and sales offers.

Powered by AI, advanced customer analytics technology finds, curates and analyzes customer data in near real time. The technology helps identify, unify and enrich all relevant data points on a company's target customers and will add necessary segmentation data.

Armed with timely and insightful customer data, companies can not only answer their customers' needs but also benefit from the ability to sell more products, lengthen their customer lists and, most importantly, make good on their revenue-driving customer retention efforts.

Source: Forbes