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Cognitive Computing can enhance the Digital Path to Purchase

February 16, 2018


Even though we have been living in the Digital Age for a few years, questions remain about how companies can best leverage big data. Billy Bosworth (@billy_bosworth), CEO of DataStax, writes, “We have to ask: Is there a missing V in the equation? Are you seeing the value from big data implementations? Most are not, which leads us to wonder why these projects are stumbling.”[1] Obtaining value from data is critical since the digital path to purchase is becoming an important channel for most businesses. To gain value, Bosworth asserts, you need three things: data ingestion; real-time data analysis; and actionable insights. Cognitive computing platforms are ideal for achieving each of those goals.


Cognitive Computing and the Digital Path to Purchase


“One of the major challenges that businesses face,” writes Romany Reagan, “is bridging the gap between the art of customer engagement and the science of data.”[2] Like Bosworth, Reagan sees the benefits of using cognitive computing, a branch of artificial intelligence (AI). She explains, “We are increasingly seeing marketers utilizing different technologies in order to maximize the effectiveness of their communications; and as a result many businesses of all sizes are exploring the ways in which advancements, such as AI and machine learning, can give them a competitive edge.” Shirley Siluk points out that AI featured prominently at the 2018 Consumer Electronics Show demonstrating more and more companies understand AI can indeed provide a competitive edge. She writes, “While AI and machine learning promise to enable whole new classes of consumer products, those smart capabilities are also becoming increasingly vital for business users. That’s especially true for marketers and other business professionals who spend their days working to find, connect with, and sell to customers.”[3]


As noted above, Bosworth insists three things are required for brands and marketers to provide customers with the experience they expect when they are on the digital path to purchase.


1. Data ingestion: Data is the sine qua non of the Digital Age and it comes in many forms both structured and unstructured. Bosworth insists the most important data is data gathered in real-time. He explains, “A large volume of data generated by countless devices, interactions, applications, programs, timelines and touch points is gathered in real time. This includes the context of what the customer is directly doing with you and real-time data relevant to that interaction (location, preferences, demographics, social media interactions, etc.).” Cognitive computing systems can ingest and integrate data in real-time.


2. Real-time data analysis: Data lying fallow in a database is as worthless as seeds lying fallow in a field. As Bosworth observes, “Not only do you need to ingest and save all the data pouring into your systems, but you also must perform immediate analysis on that data to make sense of it and give it context. This step often combines real-time data feeds with other bits of data from other sources such as legacy systems.” Because cognitive computing systems can handle many more variables than traditional analytic platforms, they are ideal for this task.


3. Actionable Insights: What brands and marketers are looking for are results. Customers, too, are looking for results. Actionable insights provide those results. Bosworth explains, “The application’s underlying data must be hyper-responsive to the customer’s interactions. You use these real-time data analyses to make in-the-moment, real-time customer experience happen precisely when it is needed. This could be via digital channels or even traditional customer service interactions, but the key is that you have the foundational data technology that makes this possible.”


Siluk cites a “2017 Salesforce State of Marketing” report that concludes, “Artificial intelligence is the leading technology where marketers expect the most growth in the next two years. Internally, marketers view AI as a means of creating more efficiency in their operations. For customers, most marketers see it as a way to get more from their data and ramp up personalization without burdening their teams.” As result, they note, “Big data and analytics play a key role of an organization as they begin their digital transformation journey in determining their success factor.”


Enhancing the Customer Experience


Siluk notes the Salesforce report concludes, “Providing personalized service is becoming a make-or-break issue for many businesses.” The staff at CIO Review adds, “It is a universal fact that if a business has a good customer service they can easily win over and top their competitors. Consumer service is the cynosure of any business as it makes them comprehend more about the likes and dislikes of the consumer, so that it can launch their right product at the right time in future. A good consumer service also helps in finding out if the customers are facing problems with their reach in terms of communication or e-commerce system. Hence, enhancing the customer service quality should stand as the primary concern for a company.”[4]


Reagan insists, “Personalized messaging needs to be a top priority for businesses that wish to thrive amidst the noise of digital marketing. By tapping into AI and machine learning, businesses can remove the guesswork involved in the most difficult aspects of personalization and CRM. Truly effective personalization results in improved customer engagement, loyalty, and spend; but only 30% of customers feel that they are getting their desired level of personalization. This highlights that, while many businesses are putting a greater emphasis on data collection and testing, they are not effectively employing the data to implement truly tailored messaging.” Because cognitive computing platforms can handle myriad variables, they are well-suited to help companies refine personas and segmentation. Reagan continues, “Machine learning shouldn’t be seen as a way to replace the marketing or the CRM team, but rather as a tool to turbo charge the effectiveness of their campaigns. It is the first real tool to enable truly granular marketing, promising more engaged customers, better conversion rates, and powerful, agile marketing.”




The CIO Review staff explains, “With big data analytics, the organizations can know which channels are often used by customers, and analyzing why they prefer and how they can improve their other sites that lacks traffic and many more. Big data also helps them to know the brands separately for each consumer groups depending on their age group. This helps them to provide additional opportunity for brands to optimize their omnichannel strategy. Big data additionally presents an opportunity to personalize and customize the customer experience.” Reagan concludes, “The more granular the customer group, the better the offer can be tailored to customers’ specific needs and wants, creating a higher level of engagement. Segmenting customers into distinct personas on a daily basis is a highly valuable practice that enables marketers to understand what makes their customers tick, and how to best interact with them by categorizing customers into different ‘lifecycle stages’, which represent the different phases that customers move through during their journey with your business.”


[1] Billy Bosworth, “Why Big Data Alone Won’t Drive Better Customer Experiences,” Forbes, 3 October 2017.
[2] Romany Reagan, “How AI Can Be Employed by Brands to Bolster Customer Engagement & Sales,” Exchange Wire, 15 January 2018.
[3] Shirley Siluk, “For Success, Marketers Need To Embrace Artificial Intelligence,” Top Tech News, 15 January 2018.
[4] Staff, “How Big Data Enhances Customer Services,” CIO Review, 15 January 2018.

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