Infuse intelligence in sales and marketing, with AI: 5 tips

Dec 23, 2021
  • sales, marketing and service
  • artificial intelligence & RPA

Who rules the world? Your customers, of course. For years, you have been learning via trade publications and marketing conferences how crucial the customer experience is. But how do you go about creating an exceptional customer experience tailored specifically to your own customers? How could this be encompassed within your limited sales and marketing budget? Our five tips will help you approach these questions in the smartest way possible. Your knight in shining armour? Artificial intelligence (AI).

Tip 1: Put ‘customer lifetime value’ center stage

We begin with an eye-opener: not all of your customers are valuable. According to Pareto’s well-known 80/20 rule, 20% of your customers deliver 80% of your profits. In other words, 8 out of 10 customers are not particularly profitable. Worse still, a considerable number of them even produce losses. Nevertheless, many companies continue to focus their efforts on all of their customers. As a result, marketing campaigns often adopt an ad-hoc approach. If a campaign simply generates new sales, it is considered a success. However, to generate more business, the investment is only truly worthwhile if these customers subsequently keep coming back. 

Enter the importance of customer lifetime value (CLV), meaning the customer’s value over the entire period in which they are a customer to your business. In order to determine their value, the historical and future profits and costs of all sales, along with any marketing and operational activities (both one-off and recurrent), must be considered. This is quite a complex task where gut feeling alone – which, in many cases, still underpins the decisions taken by sales directors and marketing executives – no longer suffices. Artificial intelligence, on the other hand, calculates CLV very simply, while also ensuring that it stays up to date.

Tip 2: Remember, AI-driven marketing is becoming the new normal

Over the past decade, ‘digital first’ had become the mantra for the sales and marketing industry. Then came ‘mobile first’. Both concepts are still crucial, of course. However, we would like to propose another: ‘AI first’. Every business – yes, even freelancers or smaller retailers – is sitting on a mountain of data. Process this with AI-operated tools such as machine learning and you will immediately gain a wealth of fresh insights into your customers and future prospects.

So how exactly does this work? The first step is to let a data scientist do their thing. Using advanced statistical exercises, their algorithms seek out patterns within your data. This gives marketing executives a clear insight into who their customers are and how they behave: what characterizes them, what drives their decisions, what is their customer lifetime value and what triggers (different for everyone) should you deploy via your marketing campaigns to achieve a higher customer lifetime value.

Tip 3: Use dynamic behavioral segmentation instead of traditional ABC segmentations

Once you have gained an insight into your customers’ behavior (and you know how valuable that behavior is thanks to the customer lifetime value), this can be applied through segmentation, thereby improving your customers’ experience – given that increasing customer lifetime value is your ultimate goal. Of course, segmentation is nothing new. For years, businesses have been splitting their customers between different segments (A, B, C or Gold, Silver, …), often based on the level of turnover generated. However, segmentation based on historical sales figures falls short when it comes to offering your customers the right products and services at the right time or via the right channel when it comes to future sales. 

For segmentation, artificial intelligence is a godsend. It analyses all (un)structured customer data and uncovers traceable patterns. From loyalty cards and POS systems to call center data, invoices, emails, shopping baskets, social media, web data and data from ERP systems, the more information, the more valuable the insights, while the more detailed the behavioral segmentation, the more effectively you’ll be able to offer your customers a personalized experience. What is more, as customers’ behavior changes throughout the year (a continual phenomenon!), they will shift dynamically between different segments, meaning that they will always fit into the most appropriate behavioral segment possible. This truly is customer-focused marketing.

Tip 4: Take a look at other areas of marketing where AI makes a big difference

Artificial intelligence can render your sales and marketing efforts smarter in many other ways:  

  • Through pattern analysis of your lost customers (‘churn analysis’), AI can be deployed to identify your customers’ churn characteristics at an early stage to help avoid possible future customer churn. We all know that looking for a new customer costs far more than securing the loyalty of an existing one. To that end, AI is worth its weight in gold, thanks to its ability to preventatively tackle such customer churn.
  • By using natural language processing, you can develop bots to answer frequently asked customer questions (chatbots, voicebots, etc.). This allows you to help your customers immediately, thereby affording your staff more time to focus on areas that provide true added value.
  • Use computer vision to improve your service provision and your customers’ shopping experience. For example, the technology can be used to search for mentions of your products and services in video images and analyze your customers’ shopping habits while inside the shop. How do they shop? Which products do they consider only to put back? Which products do they actually put in their basket before leaving without going through a checkout (for instance, Amazon Go)? The idea is to better understand your customers so that you, in turn, can serve them better.
  • With dynamic price algorithms, you can automatically adjust your pricing if, for example, demand increases or declines, or if your competitors adjust their own pricing. Applying price elasticity principles in real time will enable you to generate more profit. Airlines have been using this principle for some time now, however the potential is even greater for other sectors. Just think of the huge retailers and e-commerce platform markets that could adapt their pricing entirely dynamically based on the level of demand at any given moment. This would give these companies another way to maximize their chances increasing sales. 
  • Demand forecasting predicts when customers will move to purchase a particular product. Based on their current buying behavior, past purchases, relevant patterns and trends in the market, etc., you can predict where and when you will need to deploy sales and marketing activities to achieve your commercial targets.

Tip 5: Start using AI for sales and marketing today!

Think that your organization is not yet ready for AI-driven sales and marketing? On the contrary, we know you are ready. Even the smallest piece of customer data, be it simply your customers’ sales transactions, for example, is enough to start up your first project. Dive into your data, involve a data scientist and take an in-depth look at your customers’ behavior. Next, search for value-maximizing triggers within that customer behavior and exploit these within your marketing campaigns. You will soon notice that your AI-driven approach will both please customers and lead to a higher return on your marketing investment. Over time, you will be able to hone or expand your approach.

An open mind

One thing is absolutely essential if you want to use AI for your sales and marketing, namely the desire to change your marketing approach, allowing you to place customer data front and center. Thanks to the opportunities provided by AI, classic ‘marketing from the gut’ has undergone a major upgrade. This also means that, as marketing executives, we can upgrade the way we work by utilizing fresh insights and developing new (more analytical) skills.

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