• Conversations are naturally conditional and responsive interactions rich in buying signals
  • B2B marketers are finding new ways of leveraging conversational interactions to attract, engage, and enable buyers while decreasing barriers to entry
  • Connecting conversations across channels helps organizations deliver frictionless engagement and contextual content experiences with immediate value for the buyer

In his 1962 classic A Clockwork Orange, author Anthony Burgess creates a specialized, rhythmic language called Nadsat that’s used by the narrator Alex and his friends (or his droogs). The characters in this dystopian satire use words that are combined or permutated from other words, often influenced by the Russian language, to signify meaning and set the scene in which those characters interact. “Viddying” is to see. “Pony” is to understand. “Guff” is a laugh. This invented, informal language is purpose-driven and scenario-specific, an example of slang used by a particular subgroup to establish and confirm identity.

The specialized language used in an industry or discipline — and within a buying group — provides critical insight into how buyers are talking about their needs and challenges, where and with whom they’re talking about potential solutions, what role each of those “characters” play in the decision-making process, and when they’re most active or influential.

B2B organizations must speak the specialized language of their buyers to understand their needs and deliver the most relevant information in the moment. This requirement becomes even more pronounced for marketers leveraging conversational interactions to enable their buyers in real time.

Characterizing Conversational Interactions In B2B

Today’s empowered buyers expect interactions and information gathering to occur on their terms, whether discovery-oriented via search, synchronously via chat or interactive content, or asynchronously via email. B2B marketers are finding new ways of leveraging conversational interactions to attract, engage, and enable buyers while decreasing barriers to entry. Chatbots and virtual assistants introduce opportunities to orchestrate marketing offers and touchpoints by integrating conversational interactions into delivery channels such as web properties, mobile apps, social media, email, event platforms, and voice skills.

Connecting conversations across channels helps organizations deliver frictionless engagement and contextual content experiences with immediate value for the buyer — and immediate value for the selling organization in new buying signals generated and the actionable insights those signals contain.

However, without quality data, audience and program context — and an understanding of the information requirements and dynamics of the buying group — conversational interactions become their own dystopian narrative that fails to meet buyer expectations. Additionally, they may hurt user experience to the extent that the buyer is hesitant to engage in future dialogue.

Designing Dialogue to Activate, Validate, Accelerate Demand

The conversation is the asset the interaction type and the conversational agent — the chatbot, intelligent virtual assistant, or live operator — facilitates the dialogue inside its delivery mechanism. Separating conversations from their delivery channels enables B2B organizations to think holistically about the design, development, and deployment of conversational interactions within the program and tactic mix in a way that’s audience-centric and customer obsessed. Conversational interactions can also replace traditional forms and input mechanisms to collect data and monitor intent through dialogue and interactivity, whether with a human or a non-human entity.

The SiriusDecisions Conversational Interaction Framework provides a construct to guide the development of hyper-relevant conversational playbooks by balancing four pillars: audience, goal, delivery, dialogue.

  • Who is the target audience of the conversation, and what is known about that segment? What is known or inferred about the unique user or their persona, on the basis of how they arrived at the conversation? What are the language requirements? Consider traffic source and audience segment (e.g., anonymous, paid, open opportunity, existing customer) along with interest and intent to engage in the most effective dialog.
  • What’s the immediate goal of the interaction for both buyer and seller? Design conversational interactions to support near-term (immediate, in-session) and long-term (downstream, program-level) goals and business objectives for activating, validating, and accelerating demand. A near-term example would be deanonymizing traffic to a priority web page as an entry point into an activation program. A long-term example would be capturing key buying signals to help associate buying group members.
  • Where and when will the conversation take place? How is the conversation initiated? Audience context and buying signals should inform timing, delivery channel, and user experience to ensure relevance over intrusion and disruption. Use signals indicating fit, topic of interest, and desired behaviors (e.g., visiting a solution web page, time spent, content consumed, referral source) to define triggering events and determine optimal timing for conversational interactions.
  • Start with audience needs and information requirements to determine the most relevant dialog statements and conversation logic to track toward near- and long-term goals. For example, the conversational playbook may be informational, navigational, or focused on completing the tasks to drive specific desired outcomes, depending on context and user intent.

Conversations are conditional, responsive, and buying signal-rich interactions. Conversational interactions and their delivery mechanisms should be integrated into the tactic mix and supporting infrastructure to connect data sources, orchestrate content and delivery, and enable required routing and workflows.