The new frontier in social media marketing; harnessing the synergistic power of artificial intelligence, deep learning and predictive marketing


Tom Galido-CEO





The stakes have never been greater for organizations to remain competitive in today’s high-tech digital world. The difference today between success and also-ran requires continuous innovation and the introduction and use of new technologies to personalize, engage and communicate with consumers and target markets. Yet according to a recent IBM survey 70% of chief marketing and business development officers note that they and their organizations are unprepared for the explosion of information and data proliferating over an ever-increasing number of communication channels. This data tidal wave trend is being further reinforced by a societal fragmentation and shifting demographics which make unstructured raw digital data more difficult to capture, evaluate and act upon.

For example, Facebook’s databases ingest approximately 500 terabytes of data each day which is approximately 500 times more data daily than the New York Stock Exchange. Twitter processes about 12 times more data each day than the NYSE. These are just two of dozens of platforms capturing, producing and distributing data somewhat valuable or highly valuable to commercial enterprises, specific cause organizations and non-for profits. The challenge is to capture, classify, problem solve, evaluate and respond immediately and over a period, in a way that emulates human intelligence and converts such data into something of value.

In the commercial marketing world, marketing and technology managers were the first to recognize the power of matching Social Media, AI and Deep Learning. British fashion brand Burberry dramatically increased sales, margins and customer satisfaction by asking customers to join common social media platforms incentivized by many creative loyalty and reward programs, sharing customer information and experiences. This information led to more tailored marketing strategies, personalized customer recommendations, and valued added communications as to how best the products could be worn or used.

Not-for profits, Colleges and Universities, and other Cause-Minded Organizations quickly picked up the baton, answering the most difficult question for a noncommercial enterprise, “Why should I care?”.   Such organizations are in a continuous loop of constrained money and people resources which allow them to meet their desired outcomes such as higher student enrollment or retention, and/or support for a mission or political cause.

For example, Blackbaud, a leading cloud based software company “powering social good” supporting non-for profits, education, foundations and “change agents” including public affairs advocacy   has successfully married Artificial Intelligence, Big Data and Social Media in their “Intelligence for Good.” Their value-added strategy includes:

  • Capturing, consolidating and use of huge social-good-specific data which allows for the ability to spot and predict emerging levels of interest and trends
  • Cloud based analytics using Machine Learning and Artificial Intelligence which transforms never ending growing volumes of data into meaningful insights which are matched with marketing approaches to address specific goals. This reduces or eliminates the need for dozens of analytics staff including investment in hardware and software
  • Super charging fund raising opportunities to uncover untapped sources of contributions, support and partnerships. In recent years Blackbaud has helped clients uncover over $3 billion in partnership and funding opportunities. On any given day Blackbaud’s Intelligence for Good captures more than 40 million descriptive tags consolidated into dashboards with prescriptive recommendations for future action

Fortunately, the landscape of Big Data-Social Media technology is sufficiently large to accommodate both larger and smaller more adaptable participants. Among the large players, most recently Facebook launched and staffed a 200-person research lab dedicated entirely to advancing the field of AI. Google acquired DeepMind a company developing learning algorithms for e-commerce, simulations and games. LinkedIn acquired Bright a company focused on data and algorithm-driven job matches. Pinterest acquired Visual Graph, a company specializes in image recognition and visual search.

Among smaller more nimble companies HubSpot recently acquired Motion AI one of the top visual chatbot builders. The Company’s cross-platform technology enables anyone to create a chatbot for their site, via SMS, on Facebook, Messenger and more—no programming skills required. Other game changing social media—AI companies reinventing the marketplace for Big Data-Social Media technology include:

  • 6sense, a rapidly growing company helping Cisco, IBM and other predict sales and sales trends.
  • Arria whose software “reads” complex data such as financial or meteorological and write accurate, easy-to-read reports for companies
  • Automated Insights which uses AI to turn spreadsheets into marketing stories for sales teams




Introducing a new communication/distribution channel to compliment legacy platforms by turning intent into action


If the fortune 500 was the first to recognize the potential of social media + AI + Big Data, what is left for the vast universe of entrepreneurs advancing their modern marketing strategy?

Insights and reporting have been the first boon to the rise in data richness in social media as well as the ability to compute at speeds to make the insights available where they’re still relevant.  The challenge facing social media marketers has been the question, “So what?”.  For decades, large corporations have had access to huge amounts of customer data and the associated insights, but were never able to use these insights to drive revenue.

One approach to converting data to revenue has been to increase lifetime value by providing greater customer satisfaction through CRM marketing technologies.   While these products and platforms have extended revenues from existing customers, they have not been able to find new customers.

New customer development has long been driven by awareness advertising and branding activities.  While analysis on customers has driven creative and targeting for advertising, it has been able to do so only at a macro-level.  Artificial Intelligence (AI) is the breakthrough that has provided the “Intent into action potential” making real time customer insights valuable to solving the new customer challenge.

The wealth of feelings, expressions and information on social networks allow analytics platforms to derive meaning and intent for customers.  Rapid advances in computing speed can now deliver insights on individual consumers along their customer journey in near real-time and set the stage for AI to make decisions on how best to bring them closer to brands, products and causes.

By no means does this approach at marketing take the place of awareness marketing but it allows brands and organizations to leverage future customers who are talking about problems and opportunities in their area of influence.  For example, a legislative initiative to curb highway traffic would want to start strategically messaging to people complaining about traffic and fit a specific political profile on social media as they are commenting on social media.  Another example would be a hotel proactively giving a unique deal to a new potential customer as they are indicating that they are about to travel to a specific city. This ability to market directly to individuals on a one to one basis has always been powerful but AI combined with social media not only makes it scalable, it makes it more cost effective.

The advertising world has long been structured for the Fortune 500 to succeed.  This second movement of customer insights technologies levels the playing field to create a new paradigm… the Fortune 5,000,000.


Download this white paper (.pdf)