Generative AI in Marketing conceptualized visually

Generative AI in Marketing Isn’t Just About “Free” Blog Posts 一 It’s Time To Consider Its Impact On The Customer Experience.

“Marketing is a one-way street. Public relations, however, is a two-way street that allows communication back and forth with audiences.”

This quote echoes a message that bounced around the walls of the PR agencies I worked at early in my career. The sentiment is accurate, but its spread fell short, likely because its arbiters were PR practitioners (LOL). But all these years later, as a result of discussions on generative AI, the idea has experienced a resurgence, particularly in the marketing sphere.

These days, conversations on generative AI in marketing typically revolve around marketers coping by calling themselves “prompt engineers” and CEOs exploring ways to gut content creation budgets. 

But lurking underneath these developments is that message those old PR sages relayed to me all those years ago. The best way to engage prospects and create customers is via two-way conversation. A give and take — a dialogue instead of a monologue. 

Because for too long, organizations have been standing on a ledge shouting in one direction. And if that’s been a struggle until now, imagine the near-future nightmare ahead of us: shouting one-way messages into that same void 一 now expanded to infinity in size 一 due to the ever-growing, endless amount of garbage produced by generative AI. 

Cue the music.

As It Turns Out, Those Old PR Sages Were Right All Along 

Let’s get one thing straight. One-way conversations aren’t evil. They serve an essential purpose. They are your brand story, messaging and value proposition 一 all of which, in turn, drive your content efforts, advertising and social media output. 

Perhaps most important, they form the foundation of your SEO strategy, which is crucial for being discovered by search engines. 

So yes, while these one-way conversations are vital, it’s often presumed that once found via search, potential customers will have everything they need to make an informed purchasing decision. 

And that’s bad news for many organizations because we’re fast approaching a critical point where providing customers with the information they need, instead of the information we think they need, will be more dire than ever. 

This urgency exists because humans are changing how we ask the machines questions and businesses are simply unprepared for the shift. 

The Problem with Modern Search in the Age of Generative AI

No longer are the questions of Who, What, Where, and When the primary focus of user queries. 

For instance, an individual will typically search for products (Who), services (What), restaurant locations (Where) or operating hours (When). A request is made and information gets sent back via a one-way street. 

Searches like this are performed daily by decision-makers with purchasing power researching B2B products and services. 

But generative AI has changed the search game by introducing answers to deeper questions that tackle Why and How. Hence, generative AI is changing how we talk to the machines. 

Why and How questions require a two-way conversation, often with several back-and-forths before a user is satisfied with the response. Even with Generative Search Results (GSR) currently in use by “Big Search,” there is a ceiling on the level of information and satisfaction that it delivers.

So you’re a B2B organization. What does this all mean? 

Think of it this way. Who, What, Where and When queries are made by top-of-the-funnel prospects. Why and How questions, however, are posed by middle and bottom-of-the-funnel prospects — individuals who are serious about purchasing and need answers to deeper questions.

“Okay. But you’re a B2B organization. WHAT DOES IT ALL MEAN?!”

– You, probably

“Big Search” will always answer the simple questions. They’ve been doing it for years via enhanced descriptions, rich snippets, knowledge graph panels and everything else schema markup enables.

But in-depth answers to real-world business challenges will always be in demand. And it’s up to organizations to deliver those answers via a modern customer search experience that acknowledges search engines will always provide better answers to simple questions and highlights the importance of a smooth transition to your website where through content, demos, interactive tools and other resources, you can demonstrate the depth of your expertise and the promise of your product or service. 

Wait a second. Doesn’t that sound exactly like SEO as we’ve always known it? 

YES. 

It just requires some upgrades and a shift in mindset around what generative AI in marketing and search can mean for your organization.      

The Way You’ve Been Viewing Generative AI Is Wrong

To truly use generative AI in a way that helps you achieve strategic goals, you need to throw out the idea that tools like ChatGPT are nifty gifts to the executive gods that save money by writing free blogs and resource articles. 

If anything, modern content needs to be more in-depth, more specialized and requires more expertise. This Is how to win in modern B2B SEO. This is how prospects determine who to trust. This is how you lead them to your website. 

And once they are there, you must facilitate a two-way street search experience that delivers answers to their specific Why and How questions. Any other move shows the world you are satisfied with doubling down on a dying search and discovery model and aligning with customer preferences isn’t what you care about. 

In order to rise to this occasion, organizations must adopt generative AI as a means to add intelligent search to your website. 

To power such an application, they must tap into the robust data strategy they’ve developed, refined and perfected over the past quarter century to enhance user engagement and ultimately drive conversions. 

Yes! It’s all about the data strategy.

How Your Data Strategy Powers Intelligent Search On Your Website

Okay, Let’s assume you’re part of one of the roughly 1/3 of companies (as evidenced here, here and here) that actually have a data strategy or deliver on one. Good news — you’re on track to not be buried by generative AI. 

If you do not currently have one, while not great, there’s still time. Some resources so you can start can be found here and here

Developing your data strategy might sound daunting, but the only lift required of you and your team is gathering and organizing data that likely already exists. The hard part of this process — providing structure, making sense of the data, and delivering insights that positively impact your bottom line — can often be managed by generative AI. Don’t believe me? Just ask Amazon

Yup. I made this.

How To Think About and Maintain A Modern Two-Way Search Experience

It’s important to remember the basics of search engine optimization and how search works to understand how to best use generative AI in marketing efforts, especially when it comes to building a two-way search experience. 

Focus on Keyword Intent.

Understand the intent behind the inquiries you receive. Remember, the benefits of generative AI here stem mainly from intent keywords that capture How and Why inquiries from users. 

  • Example: The query “Why I need XYZ product for my business” can likely be addressed by the data points stacked neatly in your warehouse. However, the query, “How can XYZ product help me meet sales goals by Q4?” That inquiry should be handed over to a biz dev or sales rep immediately. 

  • Key Takeaway: It’s vital to understand when a chatbot or a human should answer a query as it could mean the difference between a quick bounce and a customer conversion. 

The Riches Are In The Niches.

An old SEO adage. This means long-tail keyword queries with commercial intent will show up far less than short-tail informational keyword searches, but long-tail keyword queries with commercial intent are much more likely to convert to customers. Ensure your generative AI responses embrace this. 

  • Example: Suppose you run a startup specializing in SaaS-based project management tools. Many queries for “project management software” will likely come in. But you need to be ready for queries such as “project management tool comparison guide” or “cost of project software for remote teams” because the users behind such queries are much further down the funnel and more likely to convert.

  • Key Takeaway: Beyond just recognizing the value in long-tail keywords, a plan for actively nurturing conversion paths is essential. These paths must be strategically mapped out with specific understanding of search intent. 

Generative AI Requires Continuous Learning.

Iteration and optimization are necessary to build out intelligent search for your prospects and customers. Generative AI applications are not static and require learning through interaction. To ensure performance, embrace this continuous learning process and aid the application by helping it adapt to the new insights it gathers and your customers’ evolving needs.

  • Example: By embracing a continuous learning and improvement mindset, an AI application has enough time to compile customer interactions and gather feedback to determine that users are most often interested in learning about the unique product features found in your SaaS project management tool. As a result, the application can adjust and become adept at delivering concise answers and helpful information that improve the customer experience and lead to more closed deals. 

  • Key Takeaway: We all want results in the form of more leads and more closed deals to be delivered yesterday. It takes patience and vigilance to achieve desired results.

Remember that the full-circle search experience starts with a one-way dialogue via search engines and ends with a chat experience on your website that uses internal data to answer the  Why and How questions that close deals. 

By adopting this strategy, businesses can align their generative AI efforts with user intent, creating a richer and more engaging customer experience. 

It will also eliminate the hundreds of hours of company-wide meetings dedicated to discussing where to place a menu icon on a homepage, since customers won’t need to manually search for anything anymore. 

Can you even imagine? That might be the biggest victory of all.

NicholasGPorter.com_DataScience_FINAL

The Data Doesn’t Lie: Secrets From The World of Data Science And Advice On How To Map Your Career

How cool is data? I just attended a panel discussion entitled, “Talk Data to Me” put on by the good folks at General Assembly.

The focus of discussion was how data drives business and product decisions across industries, but also the ups-and-downs of working as data scientist, what companies who hire data scientists look for in candidates and what it is like to be a woman in the industry. Panel members were as follows:

  • Panel Members
    • Jessica Lachs, head of business operations & analytics, DoorDash
    • Lily Jiang, data science manager, Quora
    • Laura Burkhauser, senior product manager, Le Tote
    • Ive Cojuangco, data analyst, Everlane
    • Ling Chen, data science manager, Glassdoor

I live-Tweeted the event. Below is a roundup of the most interesting insights shared by the panel members. I hope you enjoy what they had to say as much as I did!   

 

* * *

 

  •  What is your favorite and least favorite part of your job?
    • Fav and least fav part of job? Fav: working with really rich #data says @lilijiang_data from @Quora | #TalkDataToMe
    • Fav and least fav part of job? Least: having to say no to people due to lack of data says @jesslachs from @DoorDash | #TalkDataToMe
    • Fav and least fav part of job? Least: Having to make decisions really fast says Laura Burkhauser from @letote | #TalkDataToMe
    • Fav & least fav part of job? Fav: the exploration that leads to new ideas & things to fix says Ling Cheng from @GlassDoor | #TalkDataToMe
    • Fav and least fav part of job? Least: when teams put a spin your data! says @poisoniveee from @Everlane
  • Where do you see the data industry going in the next five years and how do you keep current on changes?
    • Where do you see data in the next five years? “Democratization of data within companies.” from Laura Burkhauser of @letote | #TalkDataToMe
    • How do you keep current on the industry? Online courses. Very important, even though not required says @lilijiang_datafrom @Quora | #TalkDataToMe
    • It’s important to learn from the people you work with from all different backgrounds – @jesslachs from @DoorDash | #TalkDataToMe
    • How to stay current on the industry?  Meetings w/ cross-functional teams so we can learn says @poisoniveee from @Everlane | #TalkDataToMe
  • What Skills Are Companies in the Data Space Looking For When Hiring?
    • Skills you’re looking for when hiring? Someone who can solve the RIGHT problems on the roadmap says @jesslachs from @DoorDash | #TalkDataToMe
    • Skills you’re looking for when hiring? Background in #stats, #ML & cultural alignment says @lilijiang_data from @Quora | #TalkDataToMe
    • #Skills you’re looking for when hiring? Scrappiness, #efficiency & ability to communicate says @poisoniveee from @Everlane | #TalkDataToMe
  • As you move up the ladder and focus more on people management, how do you let go of the fun stuff – doing the actual work?
    • As you climb & manage more, how do you let go of fun stuff? Identifying new #data projects helps says @lilijiang_data of @Quora | #TalkDataToMe
  • Is It Important To Discuss Gender In Data Science?
    • Important to talk gender in #DataScience? I’m a data scientist. Not a woman data scientist says @lilijiang_data of @Quora | #TalkDataToMe
    • Important to talk gender in #DataScience? Yes b/c there is skepticism of female ability says Laura Burkhauser of @letote | #TalkDataToMe
    • Important to talk gender in #DataScience? My advice: find female mentors & talk issues thru says @poisoniveee of @Everlane | #TalkDataToMe
    • Important to talk gender in #DataScience? Bonding by M & F happens differently. What I’ve seen says Ling Cheng of @GlassDoor | #TalkDataToMe
  • How Do You Empower Colleagues to Empower Themselves When It Comes To Data?
    • Making #data more accessible makes it less scary to people says @jesslachs of @DoorDash | #TalkDataToMe
    • How do you empower colleagues to empower themselves/approach #data? Empower them w/ tools! says Laura Burkhauser of @letote | #TalkDataToMe
    • How do you empower colleagues to empower themselves/approach #data? Show them how it’s done! says @poisoniveee of @Everlane | #TalkDataToMe

(Note: Some of these Tweets were modified slightly from their original form for clarity.) 

9 New Media/PR Lessons from the Experts at Boston University

I recently had the pleasure of sitting in on a Boston University College of Communication course titled, “New Media and Public Relations.”

Taught by the PR veteran/thought leader/dragon slayer, Todd Van Hoosear, the 300-level course aims to explore the effects of new media on the fundamental theories, models and practices of public relations. It also covers and uses the interactive tools that are currently redefining the practice of public relations.

Below, I’ve shared nine key take-aways from my audit of the course. These — along with several others — were shared during my live-Tweeting of the lecture. I think even the most seasoned professional can pick up something new, here:

  1. Filter bubbles = dangerous. Our info is being filtered by our friends as well as Google and FB. | #BUNewMedia
  2. Key elements of a successful viral video: brevity, humor and appealing subject matter. | #BUNewMedia
  3. You can’t guarantee a viral video. But, you can maximize its likelihood. | #BUNewMedia
  4. Videos are filmed with 1st, 2nd and 3rd screens in mind — TV, computer and mobile screen. | #BUNewMedia
  5. Pinterest and copyrighting – major concerns emerging as businesses incorporate service into marketing strategy. | #BUNewMedia
  6. Blog comment activity has plummeted in last two years. Convo has moved to social media platforms — where it’s owned by FB, etc. #BUNewMedia
  7. Blogs — really referred to as websites and news sites these days. “Blog” now really refers to content management systems. | #BUNewMedia
  8. Facebook “Like-gating” proven to be a negative engagement tactic. | #BUNewMedia
  9. PR is about telling stories. New official definition [from PRSA] does not get an A+. | #BUNewMedia

NewMedia_NicholasGPorter.com_NoahWardrip-Fruin_2012

Note: Some Tweets listed above were slightly altered from their original form for the purpose of this blog post.