Will 2023 mark the end of daze? Are we emerging from our collective stupor? Have we established a new normal? Will we treat each other better? Will A.I. bots replace creatives? To quote founding father Ben Franklin: “Heck to the no.” In fact, we think 2023 will be a year of dizzying change, sometimes wonderful, other times sobering, almost always as inevitable as the sun rising in the east. Following are three predictions and four tips for all y’all:

Predictions

1. ChatGPT and similar technologies will create jobs, not replace humans. To the extent computational devices “learn,” it’s because expert human input guides the “decisions” these devices make. Garbage in will most definitely yield that same garbage. So can you use this tech to write first drafts, press releases, blogs, social posts and emails to colleagues you’ve ignored? Yes, Virginia, you can, but you will need a pack of perspicacious writers and proofreaders to publish something that will build, not damage, your brand.
2. Metaverse development will continue, but slow considerably. In a wildly uncertain global economy, we’ll all have our hands full with the challenges of, well, reality—the technicolor universe right before our eyes (vs. behind clunky, awkward headsets). Does this mean the development of digital environments will stop? Most definitely not; the investment theses are sound, and your Gen X and Y colleagues, kids and neighbors grew up gaming in virtual worlds and are more likely to adopt this behavior pattern.
3. The music-based expression “Whoomp, there it is!” will make a dramatic return to our daily dialogue. Ok, no, thankfully, no.

Tips

1. Close the open end. During the peak of the pandemic and in the last six months of ’22, we did a bucketful, a plethora, a shipload (yes, I did that) of survey work and user testing. We learned a lot we didn’t know, validated many things we knew already and helped clients make better planning and implementation decisions. We also learned that almost every client—usually one of the senior members of the team—would rabidly fixate on one or two answers to the open-ended questions, queries that ask research subjects to fill in their own answers. Though sometimes interesting and hilariously strange, these audience-of-one answers can lead to overreactions and distract from the quantifiable trends that will drive decisions. We’d suggest eliminating these answers and replacing them with lists of options to aid recall. Capiche? If not, contact one of our archers.
2. S.E.Ohhhhnoo. Let me be honest with you, my friends (and yes, you too, colleagues). We have sometimes not done a good enough job of explaining the complexities of on- and off-page organic (i.e., non-paid) search engine optimization. For example, we often recommend that clients in this high-demand practice area optimize structure and content for words and phrases that don’t perfectly align with their core offerings. Some of the reasons why include search volumes and trending, competition and time to a measurable result. Understandably, clients ask why we’re not using the exact language that their product and brand teams use to describe what they offer. The solution to a conundrum that we know we share with other agencies and internal teams: Ground recommendations in data; make the case in numbers; provide quantified probabilities for a range of scenarios; speak directly to risk/reward ratios.
3. Collect first-party data or die. Ok, people, some hyperbole there to bait the hook. First things first: a definition. First-party data are customer data collected firsthand by a business from its customer base (vs. cookies, which are data collected by a third party). Companies must collect and operationalize first-party data to comply with evolving privacy regulations and consumer preferences regarding their personal data. First-party data are cheaper to collect, more accurate, and allow for a personalized customer experience.
4. Why use personas and archetypes in UX? These geeky targeting concepts are two slightly different ways of visualizing the same kinds of insights. Both summarize user research data: They are representations of audience clusters, capturing major areas of overlap in user behaviors, attitudes, motivations, pain points, and goals. The difference between them is in whether each one of those user types is presented as a specific human character. With personas, we give targets a name, bio, photo, and other personal characteristics, whereas with archetypes, we refer to the user type merely by an abstract label that represents the defining behavioral or attitudinal characteristics of that user type. Both allow creative teams to visualize their audience, get to know them more intimately. And both allow your bespectacled media to spend less to get a better result. And that = smart + goodness.

As always, if I can do anything for you—make a connection, share some experience, develop new nickname options—please let me know.

Thanks again for your patient indulgence.

Best,