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October 8, 2019

Should You Quit Marketing and Become a Data Scientist Instead? (Thinks Out Loud Episode 261)

October 8, 2019 | By | No Comments

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Data scientist in marketing: Team of marketers analyzing data

Should You Quit Marketing and Become a Data Scientist Instead? (Thinks Out Loud Episode 261) — Headlines and Show Notes

Given the rise of data science in marketing, whether for personalization, AI, predictive analytics, or whatever comes down the pike next, you wouldn't be criticized for asking whether you should quit marketing and become a data scientist. But is that really a good idea? Is the future of marketing nothing more than writing algorithms? Or is there a future for creative people who focus on the customer in total.

The latest episode of Thinks Out Loud looks at whether you should quit marketing and instead focus on becoming a data scientist – and how you can best succeed no matter what the future of marketing, or data, holds.

Want to learn more? Here are the show notes for you:

Relevant Links:

Subscribe to Thinks Out Loud

Contact information for the podcast: podcast@timpeter.com

Past Insights from Tim Peter Thinks

You might also want to check out these slides I had the pleasure of presenting recently about the key trends shaping marketing in the next year. Here are the slides for your reference:

Technical Details for Thinks Out Loud

Recorded using a Heil PR-40 Dynamic Studio Recording Mic and a Focusrite Scarlett 4i4 (3rd Gen) USB Audio Interface into Logic Pro X for the Mac.

Running time: 13m 33s

You can subscribe to Thinks Out Loud in iTunes, the Google Play Store, via our dedicated podcast RSS feed (or sign up for our free newsletter). You can also download/listen to the podcast here on Thinks using the player at the top of this page.

Should You Quit Marketing and Become a Data Scientist? (Thinks Out Loud Episode 261) – Transcript

Well, hello again everyone and welcome back to Thinks Out Loud, your source for all the digital marketing expertise your business needs. My name is Tim Peter and this is episode 261 of the big show. I think we've got a really cool show for you today, a lot of interesting stuff to talk about.

I want to start with a conversation I've been having with a number of marketing professionals lately around data, and what you as a marketer really need to know about data and how much you need to care about data, and I want to be really clear about this. Data is incredibly important when we talk about marketing today, you know, personalization and artificial intelligence and all of the many things that are going to make marketing more effective in 2020 depend on data.

But I think when we have that dialogue, a lot of marketers think they need to be data scientists, and I don't want to suggest that data isn't important. But what I do want to suggest is that it's not your job to be the data scientist. Instead, it's your job to ask the right questions of the data scientists.

I mean, if you want to be a data scientist, by all means you should. It's a great field. It's really interesting. You will be endlessly employable for the next, oh I don't know, decade or so. But your job as a marketer is to think about the business implications, to think about the implications for customers, to think about the customer experience.

I think of data, I think of the way companies should look at data almost like a two-by-two matrix, kind of like a BCG group matrix where the axes are on the, on the X-axis, do we have the data and on the Y-axis, do we know what questions to ask, right? And I sort of presuppose these are yes-no questions, but it clearly, it's going to be more of a spectrum.

You could do a two-by-two, you could do a three-by-three, but fundamentally it comes down to one of four positions, which are:

  1. Yes we have the data and yes, we know what questions to ask;
  2. Yes we have the data and no, we don't know what questions to ask;
  3. No, we don't have the data and yes, we know what questions to ask; and of course
  4. No, we don't have the data and no, we don't know what questions to ask.

Now I think too many companies spend their time worried about "no we don't have the data, but we know what questions to ask" and "no, we don't have the data and we don't know what questions to ask." And I think that's kind of a mistake. Now obviously if you don't have data and you know what questions to ask, so number three on my list, right? No, we don't have the data, and yes, we know what questions to ask then you need to go get the data.

But if you think about Douglas Hubbard's essential book, "How to Measure Anything: Finding the Value of Intangibles in Business," which I've talked about before, Hubbard points out a series of rules for data that include 1) you have more data than you think, 2) you need less data than you think, and 3) new data is more readily available than you think.

So if you know the questions to ask and you don't have the data, getting the data itself is not the hard part. You know, it's become very popular to say data is the new oil and I don't think that's true. Data is not oil because oil is hard to come by. Insights are the new oil. Insights require the mining and the digging and the prospecting that you would expect to do if you were actually in the business of, I don't know, going out and exploring an oil field. But you have a ton of data and typically getting meaningful answers is easier than you think it is from the data that you have, excuse me, getting new data is easier than you think it is.

I saw a really interesting thing the other day that Google will let you automatically purge data. You can go into your settings in gmail or YouTube or Google Search, and it will automatically purge data after three months or after 18 months. And what's interesting about that to me is how specific those periods are. You know, why doesn't Google let you purge data after one month? Why doesn't it let you purge it after six months? Why doesn't it let your purge it after 12 months? It's either three or it's 18. Maybe that's just easier to program, but I would bet that the recency of the data that they want suggests that the data Google collects, they've probably found gets less useful as it gets old. It loses its predictive power. So they want to keep it for at least three months so they can learn something from it, and ideally 18 months or longer, but I bet after 18 months they don't really care because it probably doesn't tell them much.

So what's more interesting is yes, we have the data, but no, we don't know what questions to ask. And for you as a marketer, that's not a data science problem. That's an insight problem. That's being able to think about how you want to help your customer, and the kinds of products and services you want to offer, and the way you want to promote that, and the channels in which you want to sell it and the way you want to price it. That's where the really fascinating parts come in. Not that data science is not fascinating, but it's the kind of thing that you as a marketer can do with a better understanding of your customers.

Look at examples of companies where success seemed obvious in hindsight. We all know tons of these questions of these examples, but why were they successful and why did it seem obvious in hindsight? Because they knew how to ask the right questions and how to formulate the right thesis about what it was they were trying to do.

If you think about Uber, they had a fundamental insight about the quality of taxi services and the utilization of black car service. You know, there were lots of cars sitting idle. Why don't we connect the driver and the rider? Yes, it took data, but the fundamental insight was, man, there's a lot of cars sitting around and man, a lot of passengers who were unhappy with the quality of the service they're getting. Obviously they followed that up with peer-to-peer. What we think of as Uber today, UberX, actually didn't come around until two years after the company started and Sidecar and Lyft really started the peer-to-peer concept, but again it came down to asking can we make the drivers more useful and can we make the passengers more happy, right? I mean that's, that's fundamentally the really cool thing.

And I want to be fair, I'm definitely for purposes of this discussion, ignoring Uber's less than savory behaviors, but the point isn't to lob at the company for its ethics or behaviors, only to note their early insight and those of other folks in understanding, hey, we've got the opportunity for a two-sided market here. How do we put those together?

If you think of Airbnb, very similar concept, this time just for hospitality. If you think of a Stitch Fix, great company understood changes in shopping behavior. People have less time, people need a little bit more support, and so just went to a very simple model that has made them profitable since 2014.

And if you go much further back, you know, look at Amazon. My favorite story about Amazon is Amazon didn't set out to be a bookstore because Jeff Bezos had some abiding love of books. But instead, according to an article on entrepreneur.com, he drew up a list. Jeff Bezos drew up a list of 20 potential products he thought might sell well via the internet, including software, CDs, and books. Now I'm reading directly from this writeup. "After reviewing the list, books were the obvious choice, primarily because of the sheer number of titles in existence. Bezos realized that while even the largest superstores could stock only a few hundred thousand books, a mere fraction of what is available, a virtual bookstore could offer millions of titles."

Notice what they said. Books were the obvious choice. Were they? I mean clearly selection played a role and clearly so did the ease of shipping books. But if it was so obvious, why didn't Barnes & Noble or B. Dalton or Borders get there first? And the answer is not because they didn't have data that would tell them this would work, but because they didn't have the insight. They didn't ask the key question that might have made, I don't know, Borders be the Amazon of today. They missed the mark and it wasn't because they didn't have the data. It's because they didn't ask the right question.

So when you're thinking about how can I as a marketer use data to personalize, or use data to empower artificial intelligence and the like, think in terms of do we have the data, and more importantly, do we know what questions to ask? Because if you can do that well, you're going to do great regardless of what happens five years down the road, 10 years down the road, and that's a much better place to be.

Now looking at the clock on the wall, we are out of time for this week, but I want to thank you again so much for tuning in. I genuinely appreciate it and I want to remind you that you can find the show notes for today's episode as well as an archive of our past episodes by going to timpeter.com/podcast. Again, that's timpeter.com/podcast. Just look for episode 261.

While you're there, you can click on the subscribe link in any of the episodes you find there to have things sent out, delivered to your favorite podcatcher every single episode. You can also subscribe on Apple podcasts, Google Play music store, or Stitcher radio, or wherever your favorite podcatcher happens to be. Just do a search for Tim Peter, Tim Peter Thinks Out Loud, or Thinks Out Loud. We should show up for any of those.

While you're, there, I would very much appreciate it if you would provide us a positive rating or review. It makes it so much easier for new listeners to find us and would mean so much to me. You can find Thinks Out Loud on Facebook by going to facebook.com/timpeter associates. You can find me on Twitter using the Twitter handle @tcpeter, or of course, you can email me by sending an email to podcast@timpeter.com. Again, that's podcast@timpeter.com.

As ever, I'd like to thank our sponsor. Thinks Out Loud is brought to you by SoloSegment. SoloSegment focuses on AI-driven content discovery and site search analytics to unlock revenue for your business. You can learn more about how to improve your content, increase your customer satisfaction, and make your search smarter by going to solosegment.com.

With that, I want to say thanks so much for tuning in. I appreciate it as always. I hope you have a great rest of the week, a wonderful weekend ahead, and I'll look forward to speaking with you here on Thinks Out Loud next time. Until then, please be well, be safe, and as ever, take care everybody.

Tim Peter

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February 19, 2019

Data is the Crown Jewels: What That Means for Marketers Today (Thinks Out Loud Episode 239)

February 19, 2019 | By | No Comments

Data is the Crown Jewels for Marketers: Marketing professional analyzing customer dataLooking to drive results for your business? Click here to learn more.


Data is the Crown Jewels: What That Means Today (Thinks Out Loud Episode 239) – Headlines and Show Notes

We’ve long talked about how data is the crown jewels for business. But what does that mean for marketers today? The latest episode of Thinks Out Loud takes a look for you. And here are the show notes:

Subscribe to Thinks Out Loud

Contact information for the podcast: podcast@timpeter.com

Past Insights from Tim Peter Thinks

You might also want to check out these slides I had the pleasure of presenting recently about the key trends shaping marketing in the next year. Here are the slides for your reference:

Technical Details for Thinks Out Loud

Recorded using a Heil Sound PR 30 Large Diaphragm Multipurpose Dynamic Microphone through a Cloud Microphones CL-1 Cloudlifter Mic Activator and a Mackie Onyx Blackjack USB recording interface into Logic Express 9 for the Mac.

Running time: 16m 30s

You can subscribe to Thinks Out Loud in iTunes [iTunes link], the Google Play Store, via our dedicated podcast RSS feed )(or sign up for our free newsletter). You can also download/listen to the podcast here on Thinks using the player at the top of this page.

Data is the Crown Jewels: What That Means for Marketers Today Transcript

Well hello again everyone. Welcome back to Thinks Out Loud, your source for all the digital marketing expertise your business needs. My name is Tim Peter, today is Monday February 18th, and this is episode 239 of the big show. I am so thrilled that you are here with this today. Thanks so much for tuning in. I think we've got a really, really cool show. I wanted to begin by building on the discussions from last week about why Google is the beast that the 800-pound gorillas in your industry are afraid of. And I'm not gonna recap all of episode 238. You can go find that on the website, or on your favorite podcatcher.

Instead, I want to talk about one of the reasons why they're such a terrifying beast. And the answer is, because they have the most data. Google over the years has collected a tremendous amount of data. Let's just start with search, they're able to make their search results better because they have more data about what a positive search result looks like. Google know what you clicked on, they know when you come back and do another search. If you're searching for something different than what you searched for the last time, or if this is just you trying to update what you just searched for to get a better answer, and then they can use that data to improve the results, and make those results even better for the next person.

And that's before we talk about Google Analytics, or Gmail, or Google Docs, right, or Android, or all of these different tools that they have to get more access to more information about the customer. So Google is this incredible beast because of the data that they have available to them. Now I've mentioned many times that data is the crown jewels in any business. It is a thing that differentiates you and allows you to compete more effectively with your customer. And Google simply illustrates that point all the time.

I've talked in the past about whether digital will turn every business into a service, and asked the question that in a digital world is every company a software company? And the answer to both is, well not exactly. However every company is a data company. Every company depends on their data to get a deeper understanding of their customer. When we're talking about data, the reason we care about it is because of the deep customer insights that it gains for us. Your data provides a more complete picture of who your customer is, what they do, and to some degree why that matters.

Now I've talked many times in the past about the fact that we shouldn't get too hung up on the kinds of data we once did as marketers. For years we looked at things like demographic data, and to some degree psychographic data, to understand what our customers were doing. So we build these sophisticated demographic profiles of our profiles as, you know men between the ages of 18-34 with household incomes of greater than $65,000 per year, and so on. But the problem with that data was that it was a picture of who the customer was, but it wasn't necessarily predictive of what they would do. It was a proxy for what we expected someone would do.

What's been great about digital for us, is we actually can see what people do. And we don't really care which demographic bucket people fall into, because the data that is most predictive of what people will do is the data about what people have done. That data is tremendously useful. And when we talk about people like Google, and Facebook, and Amazon, and Expedia, and Airbnb, and Uber, and all these folks, one of the reasons that they are so effective is because they've done a terrific job of building up data around what people do.

And that behavioral data, that predictive data, enables them to have much deeper customer insights, a much clearer picture of what customers are apt to do, are likely to do. And then use that to put the right products, and services, and recommendations, and everything in front of those customers before you get the opportunity to. That's tremendously valuable. It's tremendously important in terms of understanding what customers do. It's made even more relevant when we think about the fact that customers are now carrying a mobile printing press with them. They're carrying a mobile broadcast television network with them.

When we think about what people post on Twitter, and Facebook, and Instagram, WhatsApp, and LinkedIn, and all of these different tools that are part and parcel of their every day live, it provides the companies the platforms that provide customers with that printing press, with that HD television studio, with enormous insights into what matters. Think about the advertising business that Google has built, and think about the advertising business that Facebook has built. Why were they able to do that? Because they knew exactly what content mattered to their customers, to our customers ideally, because of the very things that people come in and tell them all the time.

Oh this customer over here likes artificial intelligence, oh this customer over here likes Italian restaurants, boy it makes it really easy to say, "Let's put an ad in front of person A about AI tools in a B2B marketing sense," and, "Oh let's put an ad in front of person B about Italian Restaurants that are new in their neighborhood," because we also know their geography. Oh and we also know the device they're on, and we also know what times of day they come online. All day, every day, that's remarkable in terms of our ability to target. And Google, and Facebook, and Amazon, and all the rest have spent years building up those capabilities. And most companies who are not those platform providers, while they've put some energies around it, it hasn't been their core focus.

Digital at its core is about data. And then using that data to understand what's going on with your customers. When we talk about artificial intelligence, AI needs data, it lives on data. And if you're going to compete as you go forward, you have to have the data that allows your AI, or any AIs you may use, to do something useful, to tell an accurate and interesting story about your customers. And if you think about any business, it doesn't matter whether in retail, or hospitality, or food service, or B2B, you have tremendous data about your customers in various places. And what becomes important is pulling that together into a wave that you can actually access it and do something with it, and learn from it.

Now I wanna be fair, you can do this wrong. There was a story a few weeks ago about Vizio, the television manufacturer, using smart televisions to track customers. To use data about what people were watching to then of course sell to advertisers. And of course we've heard lots of stories lately about telecoms selling location data. To say nothing about Facebook and all the various ways that they have frankly effed up in terms of the data that they are making public that probably most of their users would rather they didn't. So you've got to watch for that as you think about this. I don't think this can end well in the long run. I've argued in the past about why digital is like gravity, and how when you invent the ship you invent the shipwreck.

More importantly, I've talked about the fact that things like GDPR exist because marketers have screwed up, because we've made errors. We didn't treat our customers like people, we treated them like numbers. And so as you move forward on this journey, as you move forward on using data about your customers, you also need to think about how are we protecting the crown jewels. How are we using data in a way that is beneficial, and not creepy? So as you get started with this, there's a few things I would encourage you to do. First, start small, start with a pilot, start with a project that's focused on a very specific set of deliverables, and a very specific use case of where the data's going to help you.

Think about the data that you need to help customers on their journey. How are you using that data to create a better experience for your customers? You've heard me say repeatedly, "Content is king. Customer experience is queen, and data is the crowned jewels." Well this is the point, the data can only be effective as the crown jewels if you're actually using it to help your customer succeed. And I wanna be fair, yes you can sell the data to people. Yes you can use the data in lots of different ways, but if you think about the companies who are being most effective with this, they're using the data to power a better experience. And I'm looking at people like Apple. I'm looking at people like Google. I'm looking at people like Amazon. And I'm even looking at people like Facebook, who despite their challenges are designing things to say, "How do we put the right information in front of our customers so they'll stay on the site longer?"

You can argue both sides of that with Facebook, so I wanna be very fair. And I have argued both sides of that with Facebook, not everything they've done is for the better. But certainly Apple, certainly Google, certainly Amazon, they've done what they can to create a better experience, yes so people will use their products more, but also people will use their products more because they had a great experience. So think about the data you need to help customers on their journey.

Make sure this is someone's job. Who's accountable for this? Think about your team and your talents, do you have the right team and talents in place, and is someone accountable for delivering on a specific outcome of using this data. And of course when we talk about protecting the crown jewels, make sure somebody is looking out for the customer and their data. We've seen far too many news reports, far too many stories about companies getting hacked, and having issues because of this that matter, that have hurt the company's public standing, and in many cases their share price, because the crown jewels got hacked. So think about that as well, and make sure that's somebody's job.

But if you can do that all correctly, if you put the pieces in place to do this well, you will find that you are able to create a better experience for your customer, and that the crown jewels truly become something valuable to you. And that's where you ultimately want to end up.

Now looking at the clock on the wall, we are out of time for this week. But I'd like to remind you that you can find the show notes for today's episode, as well as an archive of all our episodes, by going to timpeter.com/podcast. Again that's timpeter.com/podcast. Just look for episode 239. While you're there you can click on the subscribe link in any of the episodes that you find there to have Thinks Out Loud delivered to your favorite pod catcher every single week. You can also subscribe in iTunes, or the Google Play music store, or Stitcher radio, or whatever your favorite pod catcher happens to be. Just do a search for Tim Peter thinks, Tim Peter Thinks Out Loud, or Thinks Out Loud, we should show up for any of those.

I'd also very much appreciate it if you could provide a positive review or rating while you're there. It would be so helpful to me, and it would just make me super happy, not gonna lie. I'd also like to thank our sponsor, Thinks Out Loud is brought to you by SoloSegment. SoloSegment focuses on AI-driven content discovery, and site search analytics to unlock revenue for your business. You can learn more about how to improve your content, increase your customer satisfaction, and make your search smarter, by going to solosegment.com. You can also find Thinks Out Loud on Facebook by going to Facebook.com/TimPeterAssociates.

You can find me on Twitter using the Twitter handle @tcpeter. Or of course you can shoot me an E-mail, just send an E-mail to podcast@timpeter.com. Again that's podcast@timpeter.com. With that I want to say thanks again so much for tuning in. I really appreciate it. I hope you have a wonderful week ahead, a great weekend, and I look forward to speaking with you here on Thinks Out Loud again next time. Until then, please be well, be safe, and of course as ever, take care everybody.

Tim Peter

By

May 4, 2018

9 New Insights Into How AI Will Shape Sales and Marketing: E-Commerce Link Digest

May 4, 2018 | By | No Comments

9 new insights into how AI will shape sales and marketingLooking to drive results for your business? Click here to learn more.


¡Hola, Big Thinkers! The boss is enjoying some sun, sand, and surf in sunny Mexico, so we hope you won’t object while we skip the setup this week and jump straight into this week’s round-up of 9 new insights into how AI will shape sales and marketing. Enjoy:

  1. Steve Zakur at SoloSegment wrote a really cool piece that explores the myth of automation and why it’s important to have humans in the loop. You’ll definitely want to check that one out. Steve’s post makes a fantastic companion to our look at why AI won’t steal your job but smart people who put AI to work will.
  2. MarTech Today has published the CMO’s guide to AI’s marketing impact for 2018 that’s well worth your time.
  3. One of the first things you’ve got to get right in AI is clean data, as Harvard Business Review says. They point out that if your data is bad, your machine learning tools are useless. And that’s the truth.
  4. Mike Moran made a similar suggestion in our discussion on the future of content marketing, search, and digital.
  5. Emarketer released new research that shows, despite its promise, marketers struggle to integrate AI into their workflow. That’s undoubtedly something marketers will need to address since “…[survey respondents] indicated… one of the main benefits of AI is more productivity and time savings, the top advantage cited was… it provides a better understanding of the customer.” And those benefits are too important for sophisticated marketers to pass up.
  6. Given these changes, the Sloan Review from MIT’s Sloan School of Management states that the time for retraining is now. I couldn’t agree more. In fact, we’ve put together this look at “How to Keep Up With Technology as a Marketer: The Quick and Dirty Guide” and noted that “in digital marketing, practice does not make perfect. perfect practice makes perfect” more than once.
  7. Persado offered up another way to improve with its tips on what to look for in an artificial intelligence and machine learning company as a marketer that you’ll want to check out.
  8. If you’re still not convinced of the important role AI will play in marketing in the coming years, be sure to check out this look at where AI will affect sales and marketing first—and most and these 7 ways you can use AI in B2B sales and marketing right away.
  9. And, finally, you’ve got to check out this set of 11 extraordinary insights into AI and e-commerce from the past week to wrap up these 9 new insights into how AI will shape sales and marketing.

Have a fantastic weekend, Big Thinkers. Catch you back here next week!

If you’re looking to learn even more about how changing customer behavior will shape your marketing going forward, be sure an register to receive a special report I’ve produced in conjunction with hotel marketing firm Vizergy, “Digital Hotel Marketing in a Multiscreen World.” While it’s targeted specifically at hotel and resort marketers, the lessons apply to just about any business. You can get your free copy of the report here.

You might also want to check out these slides I had the pleasure of presenting recently about the key trends shaping marketing in the next year. Here are the slides for your reference:

Finally, you might enjoy some of these past posts from Thinks to help you build your e-commerce strategy and your digital success:

Tim Peter

By

May 2, 2018

Abhi Vyas on Mobile Commerce, Personalization, and AI: The Thinks Out Loud Interview (Thinks Out Loud Episode 218)

May 2, 2018 | By | No Comments

Looking to drive results for your business? Click here to learn more.


Mobile commerce and personalization expert Abhi Vyas

Abhi Vyas on Mobile Commerce, Personalization, and AI: The Thinks Out Loud Interview (Thinks Out Loud Episode 218) – Headlines and Show Notes

Subscribe to Thinks Out Loud

Contact information for the podcast: podcast@timpeter.com

Past Insights from Tim Peter Thinks

You might also want to check out these slides I had the pleasure of presenting recently about the key trends shaping marketing in the next year. Here are the slides for your reference:

Technical Details for Thinks Out Loud

Recorded using a Heil Sound PR 30 Large Diaphragm Multipurpose Dynamic Microphone through a Cloud Microphones CL-1 Cloudlifter Mic Activator and a Mackie Onyx Blackjack USB recording interface into Logic Express 9 for the Mac.

Running time: 25m 28s

You can subscribe to Thinks Out Loud in iTunes [iTunes link], the Google Play Store, via our dedicated podcast RSS feed )(or sign up for our free newsletter). You can also download/listen to the podcast here on Thinks using the player at the top of this page.

Tim Peter

By

April 13, 2018

11 Extraordinary Insights Into AI and E-commerce from the Past Week: E-commerce Link Digest

April 13, 2018 | By | No Comments

Looking to drive results for your business? Click here to learn more.


11 Extraordinary Insights Into AI and E-commerce from the Past Week: Woman using AI to connect with customers

Hey, Big Thinkers! We’re finally getting some spring weather here at Thinks Central, so hope you don’t mind if we skip the setup this week and jump straight into this list of 11 extraordinary insights into AI and e-commerce from the past week. Enjoy:

  1. So, don’t know if you saw, but our old friend Mark Zuckerberg spent a couple of days explaining Facebook and privacy to a group of clueless old men Congress this past week. Clearly, the markets don’t seem to think the, ahem, brain trust on Capitol Hill has any chance of successfully reining in the social media giant, leading the company’s stock price to rise 4% in the last week. And, as TechCrunch points out, regulation could ultimately protect Facebook, not punish it. Obviously, we’ll keep watching this one for a bit, but until customers or a more technically-competent Congress acts decisively, Facebook’s probably going to weather this storm.
  2. That said, the role of data, tracking, and privacy clearly are getting a lot more play in the media than they were just a few months back. Which is why maybe Facebook's data problem will end up as your data problem. And that’s definitely something worth thinking about for your brand/business.
  3. All of this has much larger implications for your business than may appear at first glance. For instance, we’ve long talked about the fact that AI makes big data little. And Harvard Business Review rightfully explains that if your data is bad, your machine learning tools are useless. Expect a lot more talk around this topic over the next few months.
  4. While we’re on the topic of AI, you won’t want to miss these 8 exceptional insights into voice and AI and their effects on digital marketing from the E-commerce Link Digest series.
  5. Business Insider has a great look atAI in marketing and how brands can “leverage artificial intelligence to improve personalization, enhance ad targeting, and make marketing teams more agile.” Wow, that’s quite a mouthful. But it’s also quite true.
  6. Want to know more about the effect of AI on marketing? Well, check out these recent episodes of Thinks Out Loud, our e-commerce and digital strategy podcast. The first looked at where AI will affect sales and marketing first, and most while the second outlined 7 ways you can use AI in B2B sales and marketing. Good stuff all around.
  7. For one real-world example, Digiday put together a great case study of how Tumi is using AI in marketing campaigns, online and in stores that’s well worth checking out.
  8. That Tumi story is a great example of what marketing at the speed of digital looks like in practice.
  9. It’s fair to ask, of course, whether with the rise of the machine: “Will your job become obsolete?” as Rita Shapiro-Das does over on The Future of Commerce blog. And, given that reality, R. Edward Freeman and James R. Freeland argue over at MIT Sloan Management Review argue that the time for retraining is now.
  10. You don’t need to wait for your company to make that a priority (in fact, we’d argue that it’s probably a mistake to wait around for that to happen). We’d recommend you check out our quick and dirty guide for how to keep up with technology as a marketer instead.
  11. Finally, let’s wrap-up this week’s look at 11 extraordinary insights into AI and e-commerce from the past week — and bring all these stories together – with this set of 6 quick content marketing and AI insights and these 6 proven digital marketing trends.

Have a fantastic weekend, Big Thinkers. Catch you back here next week!

If you’re looking to learn even more about how changing customer behavior will shape your marketing going forward, be sure an register to receive a special report I’ve produced in conjunction with hotel marketing firm Vizergy, “Digital Hotel Marketing in a Multiscreen World.” While it’s targeted specifically at hotel and resort marketers, the lessons apply to just about any business. You can get your free copy of the report here.

You might also want to check out these slides I had the pleasure of presenting recently about the key trends shaping marketing in the next year. Here are the slides for your reference:

Finally, you might enjoy some of these past posts from Thinks to help you build your e-commerce strategy and your digital success: