Leveraging AI to Achieve Speed, Context and Compliance at Scale in Your Content Operations
Data and content represent the oxygen and gasoline in a modern growth engine.
This is because the 21st Century Commercial Model is increasingly centered around owned digital selling channels that rely heavily on timely, targetable, personalized, and compliant content. “New school buyers” are demanding faster, more complete, and relevant content as they engage with front line sales, marketing, and service employees across direct, virtual, and digital touchpoints.
Given this modern selling reality, customer data and sales, marketing and product content need to be treated as strategic assets. In many cases they are not. This is particularly true for sales and marketing content.
After two decades of dramatic growth in selling content budgets, these assets are generally managed like perishable inventory, stockpiles, or transitory marketing fodder. Many CMOs still focus most of their energy on optimizing the performance of paid media spend. Meanwhile, behind the scenes, the budgets for sales and marketing content – and the people and machines that create and deliver it – have grown to become the bigger part of the growth investment mix at most B2B sales organizations.
Sales managers rank the demand for more relevant and personalized content as the number one factor impacting their ability to sell in a virtual setting according to the Remote Sales Productivity Study by the Revenue Enablement Institute. And 80% of organizations are increasing their investment in content and the systems that support its delivery in context, including guided selling, next-best-action, playbooks, recommendation engines, real time scripting, and automated chatbots.
This needs to change. Particularly if growth leaders expect to generate any reasonable return on investment in sales and marketing content assets – and, to that end, the digital selling channels they support. Today, these represent the lion’s share of B2B growth assets when you add up investments in sales enablement, engagement, and readiness systems, as well as search, social media and contactless selling channels that are the mainstay of digital marketing today.
Change means tackling the real problems that have hamstrung content management and digital asset management programs for over a decade. The most practical problem is span of control. The content supply chain is a true enterprise process spanning many stakeholders, silos, and systems. No single executive can own this process.
Another problem is measurement and accountability. When it comes to content, nobody is really counting. An entire industry has evolved to target, measure, and certify media performance, yet few organizations even add up how much money they spend on content. Even fewer have financial models that link the performance of expensive digital channel infrastructure and data-driven selling tools to the content that fuels them.
But the list of challenges is even longer. Current models of content management remain largely manual, slow, expensive – which makes them inherently unscalable. This is largely due to a growing set of operational challenges associated with the enterprise process for planning, creating, organizing, assembling, and distributing content. These include:
- The increase in the overall volume of content needed to sell.
- The growing cost and complexity of creating new content.
- The speed with which that content must be delivered to clients.
- The growing number of channels content must be delivered through.
- The need to scale and personalize content globally, across segments, markets, industries, and geographies.
- And the need to manage content quality, context, and compliance.
From a financial perspective, traditional content operations simply do not scale in a modern selling model. For example, the cost of localizing, targeting and personalizing a branded content asset in five market segments is more than twenty times the cost of the original content asset according to the Forbes Publish or Perish study. Add new digital channels and 1:1 segmentation at scale, and the cost curve goes to the moon.
The combination of these issues has forced growth leaders to rethink their approaches to managing sales and marketing content across the enterprise. “Creating personalized content at scale with digital speed and control is essential but expensive and complicated unless you transform your processes,” according to Jaime Punishill, the CMO of Lionbridge, in a recent executive forum on response management. “You can’t write your way around it, you can’t anticipate your way around it, and you can’t police your way around it. But at the same time, you don’t want to pave cow paths by automating stupidity at speed and scale. So how can business leaders navigate the two?”
Progressive growth leaders are challenging traditional notions of digital asset management and sales enablement to answer that question. They are looking beyond traditional information hierarchies, writing content to spec, and establishing a “single source of truth” as the citadel and control point of all content. The most successful of them are rethinking the focus of their content efforts in the context of arming their revenue teams to answer customer questions, regardless of person, system, delivery channel, or format. This is the notion of Response Management, which looks to leverage AI and machine learning to find scalable, intelligent, and cost-effective ways to manage the quality, speed, and context of the answers across every customer facing employee, every channel, every stage of the customer journey, and every customer segment.
Patrice Trichon, the CMO of 1919 Investment Counsel, has decades of experience wrestling with these problems. In the same CMO panel on response management she emphasized the importance of using client questions and intelligence to inform the organization, governance, tagging, targeting, and compliance of content as the key point of leverage and scale in content operations.
“Managing complex, granular and real-time content is first and foremost about clients. And it really begins with how much information can we get about the client so that we can actually systematize our ongoing interaction with them. What are they interested in hearing about? What are their financial goals? Are they concerned about responsible or inclusive investing? All of that information is essential to defining what type of content we want to deliver to those clients.”
Patrice advocates taking a layered approach to create a content architecture that allows growth leaders to define, segment, organize, and manage content from across the enterprise. “We build our content architecture from the bottom up foundationally, by asking what are the critical things we need to communicate in all of our materials? What is our brand? What are our guidelines? What are the common items that exist in all of our client and selling content – whether it’s an Investment Review & Outlook, an RFP, or a fact sheet? That bottom tier is really the baseline of content about what we say about our firm, the mission statement. Upon this foundation you are creating almost a pyramid where you’re building an architecture with the ingredients that allow you to scale your content operations. So, the second layer includes the capabilities of the firm that make us unique. That includes tidbits of information, messaging, and soundbites that we want to make sure that we include. The third layer is really all of the solutions that we have to offer – in our case it’s our commentaries on investment opportunities and mapping our capabilities back to what the client or the target prospect needs. And the final piece of the pyramid, as we build up the content architecture, is really the very, very distinct, unique components of our content that are focused and differentiate our firm. So, it could be talking about topical & timely thought leadership, sharing intellectual capital, specific fund/strategy (even as granular as share class and fee structure offered) or service we offer. That allows us to personalize our content at the highest level. Creating this foundational content architecture makes that content development much easier, faster, more scalable, and most importantly more relevant to customers.”
Ultimately, some of the biggest forces driving the transformation of content management to a Response Management paradigm are demographic, according to Jaime Punishill.
“Today, half of the working population was born after 1977. That’s important because the only information paradigm they’ve known is defined by Google. Older CMOs, like me, grew up with the Dewey Decimal System, which is really about the library sciences. That’s all about ontologies, taxonomies and tagging content one way or another. It’s comfortable, but it’s a very old, manual way of organizing the content universe. And if you think about it, most of the information architecture underlying our web sites adopts this library sciences mentality. So, we’re all trying to guess how people categorize themselves, the doorway they’ll come through, the questions they’ll ask, and the buying path they will go down, “ relates Punishill. “But when you look at who most of your customers are, they’ve grown up with an ask-response paradigm. They don’t want to sort through big menus or wait for answers. They simply want to ask the question they ask Google, or increasingly now voice search, driven by voice activated devices like Siri, Bixby, Cortana or Alexa, or a human on the other end of the phone. Shifting to a response management paradigm is critical because today we have to think about how the buyer will now ask the question – and how quickly and completely you respond. That matters whether it’s answered by a sales rep, service rep, or a chatbot, or a voice activated device.”
The real value of moving from a content management to a Response Management model is that it’s inherently more scalable because it uses AI to fuel a virtual cycle, according to Ganesh Shankar, the CEO of RFPIO, and a leading mind in the evolution to Response Management. “Our clients respond to day-to-day questions. Questions from RFPs, RFQs and RFIs. But also, service questions, product questions, regulatory and compliance questions. What we’ve figured out as we add more AI to our systems, is that this can be converted into an intelligence asset. The more questions you respond to, the more you learn, the more intelligence you create to fuel customer engagement. It’s a virtuous cycle if you do it right.” Shankar points out that the distinction between content management and Response Management is important because it unlocks the potential of your entire revenue team. “This starts with the people in bid response or proposal management, but naturally extends to every customer facing employee in the business – from sales, to service, to technical support. That also applies to the contactless selling, sales engagement, and chatbot tools that use AI to answer customer questions directly or indirectly. Ultimately, Response Management scales to the degree that you can control, govern, speed up and enhance the way your organization responds to every customer question – again, not just RFPs or RFQs, but proactive proposals, presentations, security and compliance questions, product questions, or service questions.”
Meir Adler, Regional VP Sales Engineering at a fast-growing business, Walk Me, reinforces this focus on Response Management through reuse, templatization, and intelligence as ways to manage the growing cost and complexity of creating content to respond to increasingly demanding customers. “You quickly realize you can’t afford to build content to spec. Reuse and templatization become critical,” reports Adler. “There’s a learning curve to this. For us it started in bid management as we focused on simplifying and speeding up our RFP responses. In the process, we learned that 70-75% of the client questions are the same. This opens the door to templatization, libraries and reuse. Now we are looking to extend that capability to a wider range of more complex regional, local, and language scenarios. And find ways to deal with increased regulatory scrutiny.”
You can hear the entire panel discussion on evolving from content management to response management below