This article was written by myself and Dave Elkington, CEO of XANT
We are in the midst of a new global war. This is not World War 3 with weapons of mass destruction. We are not talking about the zombie apocalypse. However, the players are more powerful than governments and the stakes are higher than sovereignty. This a war with clear sides, leaders, battles, bullies, real money, and power at risk. This war is a global war over data—the Cloud Data Wars.
The Reign of Data-centric Business Models
As the Computing Cloud has become organized and ubiquitous, data has been aggregated to deliver collective, global intelligence to feed products and services that improve our lives. These new products and services generate big, big money. Data is now bought, sold, and traded as currency outpacing gold, oil, and even crypto-currencies. The players in the emerging cloud data war are the largest companies on the planet, and in many cases, they have already secretly invested billions of dollars in a race to own the most and the most important data. Much of this is hidden from the public’s view, but we have all benefitted from one of its outgrowths – Artificial Intelligence (AI).
AI has become the buzzword du jour and is being used in boardrooms, investor meetings, and in most product and sales pitches as a way to claim innovation. The easiest way to understand the relationship between the cloud, data, and AI is to consider consumer Internet applications.
Beginning with the advent of Web 2.0, most modern B2C applications are architected from the ground up with data-centric business models. Amazon knows that “people who bought X also bought Y.” Netflix knows what “people like you” enjoy watching. And, Waze knows what drivers 20 minutes ahead of you are encountering in real time. The way these benefits are delivered is simple: Web 2.0 applications collect data from every user, aggregate it, analyze it, and then contextualize it for the benefit of each individual user. Your personalized Netflix recommendation doesn’t come solely from your own viewing history—it comes from the viewing history of “people like you.” Your Waze navigation recommendations don’t come from previous trips you personally took—they come from other drivers who are on the road right now.
If AI is the engine, data is the fuel. In 1998, Google declared its mission to “organize the world’s information and make it universally accessible and useful.” Organizing all the information from the world’s libraries and archives seemed daunting in 1998—but we are so far beyond that now. Almost 90% of the world’s total documented information (data) was created in the last two years, and the pace of data creation is only accelerating with IoT.
From Hardware to Data: The Evolution of Tech Wars
In the 1980s, technology wars focused on chip speed and hardware acceleration. Players like Sun, HP, Intel and their competitors were largely concentrated in and around San Jose, California. They scrambled to raise a few million dollars to fund production runs for their latest inventions. This was the Hardware Era.
In the 1990s, workflows were encoded into software, and investment sizes grew to the $tens of millions as players like Microsoft, Apple, and Intuit standardized and scaled major categories of productivity. This was the Software Era.
By the 2000s, the Internet had arrived, and major players parallelized hardware in the cloud and transferred software to this more efficient, centralized architecture. Players like Google and Amazon and Microsoft battled over who would own the Cloud infrastructure, and other players like Salesforce and the whole of the consumer Internet took advantage of the new infrastructure to build new cloud-based business models. This was the Cloud Era.
Today, we live in the Intelligence Era, and $billion bets are placed on data. Which data is most important? Who will generate it? Who will collect it? Who will aggregate it, analyze it, and own it? In the Intelligence Era, data is the prize. Whoever controls data, controls intelligence. And whoever controls intelligence, controls commerce. The data economy is global, and control of the right data eventually means control of global sectors of the economy.
Let the Cloud Data Wars Begin
This is not a new phenomenon. The battle over data began over 15 years ago as Cloud applications began collecting and aggregating data through web technology platforms. However, the data gold rush has intensified at an increasing rate, culminating last week at the 2018 Salesforce.com Dreamforce event. No wonder the world’s largest corporations have entered the fray:
- 2016 – January: IBM buys the Weather Channel for $2 Billion to provide IBM Watson access to the global weather data asset.
- 2016 – June: Microsoft beats Salesforce in a bidding war and pays $26.2 Billion for LinkedIn and its data on over 400 million professionals across the globe.
- 2016 – October: Salesforce (among others) rumored to be bidding for Twitter to get access to global trend data (failed attempt).
- 2017 – March: Salesforce partners with IBM Watson, gaining access to global Weather Channel data among other things.
- 2018 – March: Saleforce pays $6.5 Billion to acquire Mulesoft—a data integrator.
- 2018 – September: Microsoft, Adobe and SAP announce the Open Data Initiative (ODI).
- 2018 – September: Salesforce counters the ODI announcement with its own announcement of “Customer 360”
What does all of this mean?
- It’s all about the data, stupid.
So far, B2B Artificial Intelligence has been the bubble that wasn’t. Sure, it’s fun to think about the B2B equivalents of AI-guided commerce or AI-guided navigation, but AI cannot operate without impressive amounts of data. In the B2B world, a critical mass of data is hard to come by. Since no single company has enough data to fuel AI, the launches of Einstein and Watson in B2B have been more like thuds. One can have all the AI algorithms in the world, and even a platform to run them on. But without critical mass of data those investments will go underutilized.
- Cross-company data is a requirement.
If no single company has enough data, what about “all the companies”? Yes, that would do it. The B2C world solved this by building apps that track all consumer activities and then use that collective data to help each individual make better decisions like what to buy, what to watch, how to get from point A to point B, etc. For B2B intelligence to take hold, we need cross-company data to be collected, normalized, and categorized for analysis. This allows each company to make decisions based on the superset of possibilities, not merely their own history with their own customers (the consumer alternative of which would be if you were the only driver in the world who had installed Waze).
- Follow the money.
If one were to organize the world’s B2B data to optimize business outcomes, where would one start? With cost-takeout initiatives? No. The most lucrative optimizations are ones that drive revenue. This means focusing on Sales and Marketing, which is exactly what Microsoft, SAP, and Adobe have done with their Open Data Initiative.
With points 1-3 above in mind, let’s focus on collective sales and marketing data—the holy grail of the Cloud Data Wars.
One Big Step for Tech, One Small Step Toward AI Sales
Kudos to Microsoft, SAP, Adobe and Salesforce. All four have recognized that customers are frustrated by status quo. And all four have taken a first step toward gathering more data to feed AI systems in an attempt to inform better B2B sales and marketing and better customer experiences. While it is a small step toward optimizing B2B sales, market leaders have declared data to be the prize, and they are moving heaven and earth to organize the world’s B2B sales and marketing data.
AI Value of Data = Breadth X Depth X Quality
The true value of AI is directly proportional to the breadth, depth and quality of the data that feeds it. In today’s information-rich environment, B2B buyers are largely self-educated before engaging a salesperson, and thus buyers hold all the cards. Data about buyers, what they are researching, how they buy and how they engage can give sellers an advantage when vying for limited attention and limited budget dollars. In this case, more and better data about more buyers is the key.
Silos à Singular Visibility à Collective Intelligence
There are three basic levels of data intelligence—siloed, singular and collective. Most companies are stuck with Siloed Data, struggling to analyze data stranded in diverse CRMs throughout their organization. Without systems to integrate these silos of data, companies do not have a 360° view of customers and prospects and cannot effectively understand their customers. Integrating data across silos appears to be the purpose for Salesforce’s acquisition of MuleSoft.
Microsoft’s ODI announcement and the Salesforce Customer 360 vision are both trying to deliver Singular Visibility, or insights mined from integrated data throughout an organization—a marked improvement over the siloed data status quo.
The true promise of AI can only be unlocked by tapping into Collective Intelligence—using advanced analytics to uncover predictive and prescriptive insights from the collective actions of millions of buyers throughout the world. Amazon is the best B2C example of this model, using AI-driven Collective Intelligence to disrupt online commerce and become one of the first trillion-dollar businesses.
Unlocking the Promise of AI to Fuel B2B Sales
Unlocking Amazon-like AI recommendations for B2B sales starts with data from a collective universe of buyers. Applying AI’s advanced analytics to global, cross-company, multi-CRM behavioral and experiential data helps the best performing companies develop customer and prospect understanding that has never before been possible.
XANT has understood the symbiotic relationship between AI and Collective Data since day one of our company, and we have crowdsourced the world’s richest set of 120+ billion behavioral data available to power AI sales.
As we watch the Cloud Data Wars unfold, we are more certain than ever we are in the best position to deliver on the promise of AI with our Collective Intelligence Data.
In the End, the Buyer Wins
Of one thing we are certain: the data arms race will transform buying experiences for the better. More informed buyers and sellers will be happier and more productive with fewer blind spots, less friction and fewer frustrations—three realities that plague sales today. And, as Martha says, “that’s a good thing.”
To learn more about how AI and Data, feel free to download the Frost and Sullivan Report entitled, “How Artificial Intelligence is Disrupting Sales”