The Future of Customer Engagement

Some suggest that the company was never able to fully recover from customer frustration after November snowstorms caused multiple service issues. Others claim that dips in the stock market and discretionary consumer spending, as well as the emergence of a competitors' new digital services package, all played some role, somehow. Still others tell her that her numbers aren't even accurate.

Unfortunately, this scenario plays out in various ways on marketing teams everywhere, again and again. Despite the fact that data is growing at a rapid pace and plays a central role in nearly every business on the planet, enterprises are still struggling to glean intelligence from it. Companies are reactive instead of proactive, acting far too late to identify the small problems that can become catastrophic later on. They need a faster, better, stronger understanding of data if they're going to compete, let alone survive.

Data friction within the enterprise is the key barrier to insight. According to a recent Teradata survey, 81 percent of senior business leaders want data analytics to be more pervasive in their organizations. In the enterprise, overly complex analytics technologies, restrictive access policies and over-reliance on a select few data scientists make drawing conclusions from data require multiple teams and months of work. More than 75 percent of people's time at an enterprise is spent on the fallout from this setup, including the fire drills that take place when numbers don't match up. This system isn't agile — it's the Wild Wild West.

Fortunately, we can model the enterprise after another complex system that adeptly translates constant streams of data into actionable intelligence: the sentient being. 

To be "sentient" is to be responsive and aware of one's environment. Like a sentient being, the sentient enterprise proactively takes action to prevent danger, sensing adverse events and remaining alert to micro-trends and opportunities in its environment. The sentient enterprise acts frictionlessly, as a single organism unimpeded by bottlenecks and silos — the left hand knows what the right hand is doing. Like many actions that the brain executes, the sentient enterprise listens to data and makes autonomous, real-time decisions without requiring a human's conscious intervention. (Think about how quickly and automatically a human being slams on the brakes to avoid a car accident, for example.) Sentience is scalable, extending capabilities throughout the entire body — or, in the case of the enterprise, to any sized company or database. Finally, sentient enterprises and beings both evolve through intelligence that is native and emergent. 

These capabilities enable sentient marketers to answer questions like, "What can I do to increase sales from digital?" and "How do I build customer consideration and advocacy?" Sentient marketers interact with each customer based on their profile, preferences, intentions, past behaviors and purchase patterns, taking segmentation down to a "segment of one." Communication is a two-way street: marketers engage customers, who in turn respond and provide feedback on their experiences and preferences on an ongoing basis. Automation enables sentient marketers to handle very large volumes of customer interactions without sacrificing personalization, and marketing, sales and customer care are scaled without limit.

Building a sentient enterprise and marketing capability begins with the technology backbone for analytics capabilities: an agile data platform. This is a balanced, decentralized framework that allows every person at the enterprise to access data with varying degrees of visibility and governance. For example, while data scientists with the most advanced capabilities access atomic source data, business analysts can interact with the same data through a less technical interface. They can categorize data sets by customer attribute, location, revenue or any number of criteria, all without relying on IT. 

The agile data platform breaks down silos between data scientists and marketing analysts, helping you arrive at answers faster. For example, let's say you wanted to measure how your marketing is influencing your customers at each stage in their journeys. Such information would be vital to demonstrating the value of your marketing activities and the optimization of budgets to the right channels, activities and resources. 

With an agile data platform, your business analysts could easily set up real-time tests to gauge which actions drove the highest value deals and fastest close rates. Perhaps your analysts could find out that accounts responding to marketing messages more than 11 times a quarter are most likely to close sooner at a bigger deal size. You could gain greater insight into channel effectiveness and reallocate funds to higher-yield channels. You could accurately gauge your brand's stickiness and find opportunities to increase wallet size, all without having to wait for IT to pull data for you.

Once multiple teams can access and work with data, creating a behavioral data platform that analyzes data beyond transactions is crucial. Since there will be many more pieces of behavioral data for every transactional data point, analyzing behavior requires 10 to 100 times higher data volumes.

Consider the value of responding to intent signals across all customer channels. Your customers are continuously expressing their interests through their actions on social media, digital platforms, service interactions and more. What if you could elicit intent from all your customer's behavioral data across multiple touchpoints? Understanding your customers' goals and needs would help you respond in real-time with relevant messages and campaigns. 

One of Teradata's banking customers provides a prime example of the impact that responding to intent signals can have. We helped this bank identify the likelihood of account closures by studying behavioral data — not just transactions such as withdrawals or deposits. By analyzing five months of data, including 2.6 billion events across 13 different channels, we found the typical points where customers became frustrated, such as when they called the customer service center or searched the bank's online help center for answers. The bank engaged with customers at key points in this process to ensure that their needs were met, saving $50 million in annual retention revenue and increasing their retention rate by 10 percent.

The next two stages of the sentient enterprise remove friction in both the ideation and deployment of products and processes. 

The collaborative ideation platform socializes insights across a community of analytics professionals. Think LinkedIn for analytics, where social interactions connect data throughout the organization. 

Let's say you're looking to more closely tailor your marketing activities, which currently focus broadly on your market in general and not on specific types of customers. You could create micro-segments of customers with similar attributes, and marketers throughout your company could share and collaborate on marketing campaigns for these groups. Instead of having to build a campaign from scratch for every customer target group, a collaborative ideation platform would leverage the "wisdom of the crowds" at your company to scale the marketing personalization process.  

This final stage of the sentient journey enables more tactical decisions to be made, sometimes without the need for human intervention.

Predictive technologies and algorithms flip that equation. By training computers to see changes in patterns and alert humans to the most relevant signals, humans can focus more of their time on strategic decision making that actually impacts the business.

It may seem like this capability is still far off, but we're approaching this level of sentience in our marketing every day. For example, some companies are bringing greater automation to sales with chatbots, who not only answer customers' questions and make product suggestions but also reflect the personality of the brand or product line. Soon artificial intelligence will play a central role in innovation, data access and integration, talent development and much more. As for the fear about artificial intelligence taking over these higher level management roles, Erik Brynjolfsson and Andrew McAfee write that "over the next decade, AI won't replace managers, but managers who use AI will replace those who don't."

If we set our opening story at a sentient enterprise, it unfolds very differently. A marketing analyst creates an app that delivers micro-segmentation data about which customers are cancelling their contracts. Another app designed to monitor customer sentiment sends an automated social media report to the marketing team. The report reveals that recent social posts refer to a competitor's offer aiming to lure away customers whose contracts are about to expire. These apps push all of this information automatically to the marketing team in real-time.  

The enterprise uses its automated "promotional response system" to guide service representatives during cancellation calls with this customer micro-segment. This autonomous decisioning platform accesses a database of competing offers and customer behavioral profiles to decide how to respond intelligently to each customer — whether to match a competing offer, or to let the customer go. This saves representatives time and ensures that the company retains as many customers as possible. 

The scene where the CMO gathers her team together to discuss the cause of poor sales never even happens. Because the sentient enterprise takes these automated, predictive steps, the company averts a dip in sales and enjoys strong Q4 results. 

Every company is different, and your own particular journey to sentient marketing will have its own peaks and valleys, its own landscape of opportunities and challenges. But you can still take a step forward today, perhaps by committing to changing your company's culture when it comes to data availability and access. Even a small step will help you unlock the marketing intelligence embedded within your organization and move closer to a sentient future.

Chris Twogood is the senior vice president of marketing at Teradata.

Source: Forbes.com

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