Across audiences and demographics, in whichever industry you might work, conversational interactions are becoming increasingly embedded in the digital experience, as buyer, customer, partner, and employee preferences shift to self-guided interactions at each stage of their journey.
Marketers’ ability to reach, engage, and enable B2B audiences means something different to every business based on what they offer, how their buyers buy, how customers adopt the solution, and how they engage post-sale. Understanding and connecting with these audiences through dialogue in a way that ensures immediate value requires an understanding of that interaction’s intent, as well as the many different sources of direct and indirect influence.
In the not-so-distant past, marketing looked something like this: We had a plan, we deployed the tactics, and then we measured them as best we could. Once they were in market, we didn’t have a lot of room to adjust on the fly or in real time. Things were really set as they were, though we had a few smart decision points programmed into certain sequences. Years ago, marketers often had to work in a “set it and forget it” fashion, until we got back into the diagnostics phase.
When marketers look at our new digital reality, we see that the buyers and customers are really the ones leading the stance. The right content — or what’s most relevant and meaningful to that audience — is not an absolute concept, but that’s going to change with each interaction based on new information obtained, and on new experiences with that selling organization or inside of that buying group. Marketers’ goal then becomes to meet buyers where they are and enable that next step in the journey as a group. This requires the ability to sense and respond to buyer needs in real time to provide a highly relevant, optimized experience by understanding which tactics we need to activate, and how we need to tailor those tactics for that local market.
As modern marketers think about enabling our empowered B2B buyers with AI, we need to be able to translate all of this engagement with digital and non-digital tactics into actionable insights, and we need the technology and the data to support that. AI and automation play a big role here on the infrastructure side.
Virtual assistants for B2B marketing need the conversation skills to support that full lifecycle to enable sellers and partners, improve the digital experience for all of those audiences — whether internal or external — and to provide consistency in context in audience interactions across delivery channels. The conversation automation technologies that power these virtual assistants must be able to pass conversational data, outcomes, and intent signals to other marketing and sales systems and data sources in order to continue to drive this contextual awareness for customer- and partner-facing interactions and ensure precision and scale, as we think about how to get that work done.
Marketers can improve the AI customer experience by embracing effective new technology and the role marketing virtual assistants can in their business.
By intersecting technology, insights, creativity, and culture, AI has fundamentally changed our ability to understand and empower our bespoke audiences, whether they are customers or employees.
To understand how AI improves the customer experience, here are five PX use cases for virtual assistants:
b. Program management
a. Local marketing
a. Best content
b. Best placement
a. Co-op balances
b. Data updates
a. Frictionless engagement
b. Personalized outreach
Watch the full webcast, Drive ROI With AI: The Future of Channel Marketing With a Virtual Assistant. Or, Contact BrandMuscle to find out how Markie, the industry’s first local marketing virtual assistant, will drive program utilization and enhance customer, partner, and employee experiences with AI and machine learning.