The future of online shopping gets real with AI and machine learning
AI and machine learning have starring roles in the future of online shopping. Retailers that leverage these technologies effectively can build brand loyalty for years to come.
Welcome to the sweet sixteen episode of In a CX Minute.
Has been a very interesting time here at Narrative HQ ™. We’re really cooking with gas now, momentum moves us forward relentlessly, and all those cliches.
Before we get into what the narrative work is demanding, let me share a little bit of what I am researching / doing so you can get an idea of what goes into the shaping of a narrative (value proposition, positioning, message, correlated outcomes, and more – but besides that, where do the ideas come for the narrative).
Wondrous Jenn, the heaven-sent editor for this site and the newsletter, will be mad at me because I picked my own lyrics this week – but I can live with that for one week (and hopefully so can she).*
I put a link to a great paper on AI last week, one that explained why it is so hard to get AI right. It said that most people embraced AI without really understanding what it is, or how it works, or even what are the benefits it can bring. I nodded emphatically as I was reading that, and I hope you were too, and aligned that with my previous sharing of data that justified that most people are doing it, but not enough understand it or see value in it (read last week’s episode for more details and data).
I found this chart in a report published by FICO (yes, the credit score people – among other financial tools) called The State of Responsible AI: 2021. In this report there is a lot of good data and analysis about building models, biases, ethics, and plain simple what we are seeing and doing with AI.
If you’re doing AI in your organization, and most of you are, then you should read it for the analysis as well as the data.
To me, it is more of justifying the fact that we are going on an interesting journey with “AI” (I said last week that is it not AI, just ML – but that’s a different discussion): with only 11% of organizations using AI just starting their journey – we are in the absolute mainstream stage of market adoption for AI.
We will, obviously, spend more time on this moving forward – but for now, know that – well, that AI adoption in the organization is wide-spread, and poorly done. And yes – I question the origin or definition of “advanced” AI implementation – but what this data point shows is that AI is starting to move past the “lab or skunkworks” stage into the deployed and adopted stage. And if that is the case – the stats I quoted last week (32% of customers see the value of what organizations are doing, and 14% of companies think it is reaching their goals) are not very encouraging.
And that is also if you get past the concept that what we’re doing it not even AI (even if we call it that) … but I digress. I’m not against AI – I am against organizations spending necessary resources in badly implemented, poorly understood advanced analytics that won’t return a result.
AI and machine learning have starring roles in the future of online shopping. Retailers that leverage these technologies effectively can build brand loyalty for years to come.
Let’s shift our thinking a little – let’s talk about turtles and bridges.
No, not talking about LOGO (‘member?) and how to learn to program (DOWN 2, TURN 90, RIGHT 1, etc. – if you don’t know what I am talking about, you may be a tad young…). I am talking about building blocks, foundational elements – this is where it all started.
I was watching TEDx talks and came across this gem from Ranger Nick (Nick Furman, educator and wildlife advocate) where he is doing a presentation on what good teachers do differently (it is a good video, you should watch it if you have 20 minutes – edutainment at its best) and around the sixth minute (in case you want to know why I am talking about this) there is a scene with a turtle where he explains how this specific breed of turtle is a keystone breed. He talks about specimens for every type of animal and plant that are “keystones” – foundational types that make or define a specific genus.
A keystone (or capstone) is the wedge-shaped stone at the apex of a masonry arch or typically round shaped one at the apex of a vault. In both cases it is the final piece placed during construction and locks all the stones into position, allowing the arch or vault to bear weight.[/h3]
The concept made me ask myself if we have similar components in CX. Are there keystone elements that make CX work better?
Doing some more reading on architecture and keystones, I learned that it’s a key piece that builds an arch, a doorway, a bridge. Now, this is starting to come closer to where we are: we’re in the process of transitioning from traditional CRM and customer-360 models of customer relationship to a CX and customer-determined model of interactions – and as any good transition, a bridge makes sense here…. Could it be possible then, me asks me, that we have a keystone to this bridge – a foundational element that helps us move from CRM to CX?
The answer is “it depends” or “it’s not that simple” or, plainly, “yes” depending on how you ask the question, or where you are coming from, or what you define as CX. However, deeper thought spent in this area concludes that whether you are deploying a B2B marketing automation solution, or a D2C commerce-led, insights-driven infrastructure the answer remains the same: data is the keystone for CX initiatives.
I know, I know – this is not a revelation, I cannot stop talking about data as the core element for everything… but this is further validation, and a new way to talk about it. When it comes to the work we do here at Narrative HQ ™ – finding new and innovative ways to tell stories is a – well, a keystone of our mandate (see what I did there? Awesome sauce)
For decades, brands have chased the goal of creating a 360-degree view of the customer. It hasn't worked out so well, and now there’s a better, faster, more agile way to gain customer insight and improve CX.
I can hear in the back of my head the admonition of Wondrous Jenn (no, not about picking my own headers or about doing my own callboxes – but about the length… “come on, dude – everyone expects to read this thing in a minute… wrap it up!”) about this contribution – so I am coming down for a landing…
The last piece is more of an admonition, a warning than anything else.
I recently came across an “old” (if you can call anything from 2020 old – but given COVID, I think we can) attempt made by Gal Gadot during the pandemic to lift people spirits. She thought it would be interesting to get diff celebrities, people she was in contact with (virtually) to contribute to a big sing-a-thon of John Lennon’s imagine. I truly applaud the effort, even more in context, but the approach is what got me thinking about a valuable lesson.
The result was not very good (why try to be nice) even if they thought it was. And the reason for this lack of luster was the fact that everyone was allowed to do what they thought was better aligned with the original effort of bringing people together (one more time, applaud the effort – even more so in context).
But you know me, I am nothing if not a single-mind thinker – so I was trying to figure out how we can get a lesson for CX here? Well, as it turns out – if you think the way I do this is mostly resembling of a CX project at virtually any organization, at least in its first iteration.
This is not a criticism of the video, or the effort – but a cautionary tale to those of you starting your CX initiatives – don’t let them become a bad meme. Know what it needs to look like before, and don’t be afraid to make the tough calls. Make sure you know your stanzas and what the strophic song should sound like at the end.
And with that, talk next week. Ping me or reach out with your reactions. Looking forward to the conversations.
Toodles.