You may have noticed in your last several leadership meetings big changes are happening in B2B Sales and Marketing. The process, data, and technology for how B2B revenue is generated and how the purchase process happens are rapidly changing. These changes are driven not only by the types of software-driven solutions and services B2B organizations are purchasing today, but also by how revenue teams work with prospects and customers.
For context, let’s quickly recap the current buyer-seller relationship and revenue generation process. B2B buyers stay anonymous conducting digital-first research, making it more difficult for B2B sales and marketers to identify prospects and customers. This translates into revenue teams spending hundreds of hours trying to figure out which buyers and accounts may or may not be a fit. Even after a new customer’s initial purchase, the focus immediately turns to customer renewal and solutions’ cross-sell/upsell. The revenue generation is now concentrated on the full customer lifecycle and lifetime value of the relationship, not just winning new customers. These B2B dynamics are creating a need for a smarter way to generate revenue and creating delighted, long-term customers.
The Rise of Revenue Technology
With today’s buying and selling process dynamics, B2B teams are re-thinking the whole revenue process. This re-think includes how to identify, engage, delight, generate, and expand and renew customers. B2B teams are hyper-focused on breaking down the people, process, and data silos between departments to better:
- Model and identify prospects in-market for their solution right now.
- Engage ideal customer profile accounts and buyers who are a fit for the solution.
- Appeal to the right buyers by delivering more tailored experiences and information.
- Arm marketers and sellers with account and buyer intelligence to better aim their effort.
To help automate and scale this effort, B2B executives are turning to technology. In fact, deploying new and integrating existing technology is becoming the enabler of modern revenue generation for cross-functional teams (Sales, Marketing, Customer Success, Operations, for example). The industry has even given this market category a formal label: Revenue Technology or “RevTech.” Revenue Technology refers to the collection of technology, data intelligence, processes, and decision-making support aimed at intelligently generating revenue across the full customer buying process. Previously, most organizations approached revenue generation from a Sales or from a Marketing perspective, and then tried to “align” these efforts. This approach has proven to be limited and is highly inefficient.
Much of the marketing and sales technology being used today has shortcomings, is siloed, and does not map to the way buyers and companies make purchase decisions. For example, popular marketing automation systems lack the capability or intelligence to move beyond basic lead generation, which is just one part of the revenue generation process. Sales Technology is no different. Customer Relationship Management (CRM), the core system for most B2B organizations, was not built to facilitate intelligent decision-making. Rather, CRM was developed to store and organize customer records.
These incomplete, disconnected systems for Sales, Marketing, Customer Success and Operations force teams to spend precious resources on optimizing data and functional silos. It is important to note that these systems are often still part of the revenue technology system, just not at the core of today’s modern revenue generation process.
The leading high-growth, mid-market, and enterprises teams are collapsing silos by applying revenue technology to grow customers and revenue. RevTech is also poised to deliver better buying experiences aligned with individual buyers’ and the collective decision-making teams.
As always, a word of caution and reality that seems to come with every new category of tech: Technology can be an effective enabler, automator, and scaler of strategy. But, if the company’s revenue strategy is off, technology is not going to fix a bad strategy.
RevTech Delivers the Full Customer Lifecycle and Lifetime Value
Many B2B organizations focus so much on new customer acquisition, they often neglect the real opportunity—expanding current customer relationships to grow revenue and relationships. While “net new” customer acquisition is critical for business growth, ignoring existing customers can leave a significant amount of revenue and profit on the table. This is especially true in today’s digital-driven world where companies purchase software, tech, and/or services via subscription. Often referred to as software-as-a-service (SaaS), this model provides agility and lower overhead for the B2B organization by accessing solutions in the cloud. This means much lower overhead to manage and freedom of choice to move providers based on best fit and performance.
For the vendor, the subscription, hosted model allows companies to capture annual recurring revenue (ARR), generating more profit over time. However, the subscription ARR model does not come without vendor risk. Vendors must renew the subscriptions regularly, usually every one to three years depending on the vendor-buyer agreement. This is where revenue technology and the data, process, and people working in tandem can become a significant asset to an organization’s revenue growth strategy.
Predictive, Intent, and Propensity Data and Models Are Core
At RevTech’s core are artificial intelligence (AI), machine learning (ML), and big data to provide data and decision intelligence for every professional involved in a company’s revenue generation process. Data and decision intelligence are applied throughout the entire process to inform the revenue team on the right accounts and buyers to engage. This intelligence also recommends the appropriate information and content to share with buyers at the right time. In turn, the data intelligence effort provides a much better buyer experience providing more relevant, useful information. The outcomes are often accelerated purchase cycles, more efficient purchase processes, and more satisfied customers.
To bring the power of data to life, here are a few use cases where Revenue Technology is being applied today to positively impact revenue generation efforts.
- Predictive machine learning is deployed to identify which accounts are the right ideal customer profile and those accounts that have the highest propensity to buy. These models also are used to identify which customers will be most likely to be loyal and successful customers, based on the data.
- AI is used to generate buying intent signals about which accounts are in market, based on aggregate engagement across specific topics, content, and channels. These data signals are also used to activate what communications and outreach are initiated to the appropriate buying committee members at the account.
- Big Data with AI and ML is used to generate actionable information about both the buyers and the accounts the revenue team is pursuing. This information is used to build buyer and account profiles that are relied on to develop account strategies used by the full revenue team to pursue the account.
Revenue Technology holds tremendous promise to more efficiently and effectively generate happy, profitable B2B customers. With advances in AI and Big Data leading the way, machine automation can be uniquely combined with human innovation and existing systems to better serve today’s more sophisticated B2B buyers and their changing needs.