7 B2B marketing uses for artificial intelligence
Artificial intelligence has been a hot topic of discussion among clients, peers and coworkers for some time now. Even though it’s being explored and discussed constantly, I’ve found that there aren’t a ton of tangible examples of AI explored in the professional services world. Knowing this, I challenged my team of developers, marketers, strategists and creatives to share AI ideas designed specifically for the PSO space. Check out just a few of my favorite submissions below.
Use AI for internal experience search
One way to begin using AI is to create an internal tool (something similar to a chatbot) to help internal folks search their experience, people and insights databases.
Many of our clients ask us to build out sophisticated search and filter functionality on the front-end of their websites because, “internal people need it to find a lawyer who has experience in X field and is licensed to practice in Y state and graduated from Z law school.”
From my perspective, this ends up adding a lot of unnecessary bulk to the front-end user experience and design of our sites, all when we know that the majority of external users don’t ever use these advanced search features.
So, the idea is to use AI to create an internal tool to search these databases, keeping those client needs and internal audiences in mind. The use of AI would allow the results to refine and evolve over time as it’s used. I could even imagine building an app or PWA that uses voice to search this tool. This whole idea is similar to something I included in a past Experience Lab talk.
Use chatbot to personalize thought leadership and “push” content
I was thinking about using a chatbot that could ask a site visitor a few quick questions or take them through a quiz in order to tailor the thought leadership topics shown to them. This could also follow up with push notifications when new content is published that fits their interests.
Design voice directories for basic professional and office information
First and simply, I think the industry could find a lot of value in voice directories for basic professional and office information on the major platforms like Alexa, Google and Cortana.
Use AI for recruitment and interview scheduling
When reviewing recruitment interview scheduling, it’d be interested having AI work to set up interview slots automatically. Consider the boost of efficiency!
Analyze content for brand voice and consistency
When considering improvements to the quality of a website’s content, the Hemingway Editor is a fun example of AI in content writing. The tool generates a “reading grade” level by analyzing the use of adverbs, qualifiers, passive voice and complex words in copy.
We have used this tool for content audits, and in the future, I expect more tools will be available that allow content writers and editors to refine the scoring model (e.g. evaluate if content aligns with a brand voice or identify business jargon and recommend more descriptive prose).
Create recommended content without supplied categories
I can see a use case for “recommended” or “related” content. Think: “suggested reading” after a piece of content, etc. Right now, recommended content is normally based off of fairly simple relations (this is code lingo for you marketers out there) that aren’t always perfect, but if the network was trained to recommend content based off data (received from a user), there’d be no need to rely on supplied categories.
There’s a phrase I heard that I find useful when thinking about AI. It is much easier to train AI to recognize pictures of dogs than it is to train AI to draw a dog. Translation: anything based on distinguishing trends from data is a more realistic problem for us to solve.
Combine historical marketing and web analytics data with current web traffic to identify right-fit messages for 1:1 marketing
Sparked by recent marketing talks, I imagine it’s possible to utilize historical marketing data and analyze it against current web traffic and analytics. Web data provides information regarding referral traffic, organic search, who is looking, and where are they coming from. In conjunction with that data, we can begin to include current and prospective client data including financials and recent events (mergers, acquisitions, leadership changes, etc.) to determine high-profile clients susceptible to specific messaging.
Ideally, the AI would be able to determine the key patterns of what makes a client more likely to engage in repeat business, allowing business development and marketing efforts to become more streamlined and personalized.
It’s pretty clear that the folks at One North have plenty of ideas around how artificial intelligence can and will be a powerful tool for digital marketers in the near future and the now. It’s exciting to think that digital user experiences will continue to improve, leaving room for our brands to tell deeper stories, allowing us to connect with our audiences more authentically and with more ease.
If you’d like to learn more about how AI can improve your digital experiences, contact us.