Dealing with customers is harder than ever, but more profitable than ever. Customers want omnichannel service and can access competitive information, more than ever before, anytime, anyplace, on the Internet.
Brands, no matter their size, need to be more proactive in anticipating customer demands before they start shopping around. Luckily, almost every brand today has a treasure trove of customer information available to them — transactions, marketing communications, onboard telemetry, voice and text support communications. The list is endless. They also can access external data — macroeconomic, social sites, and the Internet at large, blogs, influencers, etc.
How on earth can you curate this vast amount of data, organize and make any sense of it all? Well, the latest marketing and sales technology platforms, based on sophisticated AI, can analyze every customer journey, one per customer, cutting across the traditional customer silos — sales, marketing, support. Gartner calls this customer journey analytics, others say personalization. Either way, artificial intelligence can be used to organize this data and use it to understand customers better.
AI models can now analyze the billions of patterns inherent in a diverse customer dataset. Analyzing which marketing actions will work for each individual customer. If a customer buys a product, how likely is it that other similar customers would do the same? Multiply this process across all your customers and you soon have billions of possibilities, requiring trillions of calculations. The magic is in automating this process, from data ingestion to processing actionable insights.
Replacing Obsolete Tools
Employing the latest AI, marketers are now able to automate the processing of customer experience data, and then value and measure customer engagement — the customer’s view of their commitment to your brand and products.
Not only replacing the need for Net Promoter Scores (NPS), but more importantly, bringing customer engagement to the forefront of a business’s drive for customer success and financial results. Managing customer experience (CX) has seen massive changes in the past few years — the explosion of data, faster channels for selling — technology has made driving financial results more complex than ever, while the demand for financial results has never been greater.
Any marketer who is building customer journeys needs to incorporate all manner of customer data into their campaigns, based on availability and relevancy. Some of this data is buried deep in ERP systems, some come from marketing campaigns, sentiment studies, web traffic and external sources — such as macro-economic reports, social media, blogs, etc. Only by combining these sources, can a marketer gain a true, composite view of a brand’s customers.
Remember, customer engagement metrics are not systematically used to decide customer offers driving both engagement and financial results at the same time. So, why do marketers engage customers and ignore these factors for driving financial growth?
The actual process of turning data into actionable insights is undeniably complex and requires a multiple-stage orchestration pipeline, from data collection and input to UX. So, “rules-based” and “AI/lite” based analysis and insights are not going to cut it. Neither will a single Next Best Action (NBA) generate the results that are needed by large-scale enterprises to drive financial results.
Actively engaged customers spend more money, participate in branding initiatives, and often become your company’s best brand advocates. Therefore, you need to devise engagement strategies that would keep the existing customers engaged and make them the best advocates of your brand. To engage, you need to understand.
Experts use different terminology for Customer Journey Analytics (CJA), but in the end, everyone now believes that one customer journey cutting across traditional business silos is a total game-changer.
Now is the time to break down your organizational data silos and to start sharing. You may struggle with the scope and scale of the data that suddenly becomes available. But it all starts with the data. By leveraging your own customer data (not all of it, but just the right amount that helps move the needle), you can start to measure customer engagement uniquely and drive improved financial returns.
Jean Belanger is the CEO of Cerebri AI. To learn more about Cerebri AI and the Cerebri Values Customer Experience platform (CV/CX v2), please visit www.cerebriai.com. Before founding Cerebri AI, Belanger started three companies including a VC fund, programming tools vendor Metrowerks CodeWarrior and data science supply chain software provider Reddwerks.