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Monday, May 1, 2017
What your paid search KPI says about you
Every advertiser measures success based on key performance indicators (KPIs) that they deem relevant. Columnist Andy Taylor asks, What do your chosen KPIs say about your priorities?
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How to Manufacture Urgency to Blow through Conversion Roadblocks
We don’t need things.
We might need a six-dollar, almond milk, sea salt caramel mocha (no whip) when it gets a little chilly outside.
But we don’t need-need.
The lights are on. Roof over our head. Heating or AC blasting in the background.
That applies to most things you’re trying to sell.
Doesn’t matter if we’re talkin’ ‘bout that shiny new app you deployed or the fancy new eComm product. People don’t need it.
Which makes your life tough. How are you going to move the needle, get more subscribers, and scale revenue, when the vast majority of the people you’re speaking to have zero actual need to buy your widget?
You need urgency. Or more specifically, you need to manufacture urgency out of thin air.
Here’s how a few of the web’s top converting sites create urgency out of thin air to get visitors to finally commit once and for all.
Why Urgency Works
People don’t need your stuff. But it gets worse. Because people also resist change at the same time.
So you’ve got two problems. You need to shake people out of their inertia. And then somehow get them to act.
Thankfully, the solution’s no secret. There’s a book on it. Along with countless studies.
For example, ConversionXL explains one account where just a little bit of urgency sprinkled onto a product page lifted revenue by over 27% for Bob & Lush.
They came up with the idea to that “clarity of deliver time on a product page would push more customers to convert.”
Sound familiar? It’s what some of the best in the business, from Amazon all the way down to the QVC have gone to great lengths to employ.
So they made one relatively small tweak to their product pages.
The new variant included a little simple text box that highlighted when someone would receive their product if they ordered within a short time frame.
Not only did revenue jump (27.1%), but the the number of purchases (9.5%) and checkout visits (10.1%) did, too.
Of course, the inclusion of this delivery date estimate wasn’t just a hunch. An epiphany. Or a ‘growth hack’ some growth hacker wrote about in their Bible to Growth Hacking on GrowthHackers.com
Instead, the hypothesis came from a place that good ideas always flow. But few rarely tend to go.
Consumer Research (AKA The Part Everyone Always Skips)
In 2012, Marcus Taylor of Venture Harbour launched a ‘Groupon deal for musicians.’ (And wrote about the experience in another excellent ConversionXL case study. Yes, I’m completely ripping them off today).
He reportedly invested months and even dipped into personal savings to fund it. The boats were burned. There was no going back. It had to churn a profit.
No need to bury the lead. He increased conversions from a mediocre-but-fine 2.5% up to an astonishing 10.8% by infusing urgency into every pore of the site.
That incredible conversion lift wasn’t the part that got me, though.
This was:
When people think of conversion optimization, they go to landing pages. They go to headlines. CTAs. Images. And other similarly miniscule details that kinda don’t move the f-ing needle.
But all of those elements (which we’ll touch in soon) are at the mercy of one giant thing: the audience.
All of the CTA tweaks in the world can’t save you from targeting the wrong audience in the first place.
That’s the critical difference Marcus understood. And acted on. (Emphasis, mine.)
“Prior to launch, I “tested” hundreds of traffic sources, from Reddit Ads, to specific music forums. I wanted to know was which traffic sources I need to prioritise during the real campaign.
I ended up with a custom Google Analytics dashboard like this, which made it clear which traffic sources delivered the most relevant traffic.”
“Not only did I know where my customers would come from ahead of time, but I knew more about my audience, such as how guitarists were almost three times more likely to buy than drummers, and that my conversion rate was highest in the UK and Australia.”
Similarly, when ConversionXL worked with Bob & Lush initially they didn’t haphazardly start throwing stuff on a DIY landing page builder. Rather, they begun with a boring, tired, old survey.
One hundred eighteen people opted in. And many agreed that their biggest fear centered around “running out of food for their dogs.”
That’s the catalyst. The trigger.
It manifested as a purchasing roadblock based on “knowing when the food would arrive.”
So that’s what ConversionXL leveraged. You’ve already seen the updated landing page variation that was a success. Just by using simple language to entice people to buy now (instead of waiting around).
The tactic – the thing you see on the screen – isn’t the point. It’s the impulse it targets. The underlying motivation that’s already preventing people from feeling like they need your thing.
It’s no coincidence that this is the exact same strategy that one of the interwebs top converters implements.
Expedia recently announced gross revenues of $16 billion. Up 8% from online sales.
Which should come as no surprise when you see what they’re doing.
How Expedia Manufactures Urgency Out of Thin Air
Visit Expedia.com.
The homepage is fairly bare. A giant reservation form takes over almost everything above the fold.
Below that, a few of “Todays Deals” are highlighted.
So far, not much is happening. It’s not until you actually search for a trip that things start to get interesting.
Vegas sounds fun. Pool season sure beats reading another blog post like this in your pajamas.
Plug in some dates. Hit Enter. And here goes.
Whoa. Lots happening.
You see plenty of greens (good!) and reds (bad!) to help you instantly understand their meaning.
In the lower right-hand corner, multiple little callouts keep popping up, sliding in and out of the screen, emphasizing the same thing: a BUNCH of other people are looking at booking these deals right now – so they might not last long.
Then of course, the Daily Deal hits you at the top of the screen. A classic countdown timer that ticks away. My heart rate sped up. Palms sweaty. Despite not having any real interest in booking this initially.
Once again, that was no accident. As this case study featured on Behave.org (formerly WhichTestWon) indicates.
All that was added was a countdown timer. That’s it.
They even removed a few elements, including ‘free delivery’ and ‘order now’ in order to remove extraneous distractions and focus viewers on what mattered most: that countdown timer.
The result after 50,000 viewers? An instant 8% conversion lift.
Ok. Enough boring marketing stuff. Back to Vegas.
How Expedia Uses Price Anchoring & FOMO to Make this Trip Look like a Steal
Those FOMO callouts slide in and out of view.
The countdown timer continues ticking down. And then the product attributes help you decide.
For example, scroll down a little bit until you reach Cosmo.
It’s garnered a little yellow “Top Hotel” badge. It literally screams “Wonderful!” with excellent ratings and reviews to match.
Price anchoring in full effect, with the ‘sales price’ slashed down to the new effective one.
Scarcity comes into view with the strip of text in red that highlights the number of people who also booked this hotel in the past forty eight hours. Along with when it was last booked.
So. If we’re even remotely serious. We need to move fast.
Let’s select Cosmo. Because c’mon: wraparound terraces!
You look at available rooms and are immediately met by an “Unreal Deal” that will “save you 100% on your flight.” That’s backed up by the pricing, which shows you’ll ‘owe’ $0.00 more to select it now.
Deals like that won’t last. Don’t last. Which means you should act.
Not later, but now.
How Expedia Forces You to Take Action (Now)
Words matter.
It’s not that people absorb every letter in detail. They don’t. Hell – people don’t even read. ‘Specially not online.
But the sum is greater than the parts. It’s scanned in a moment’s notice and the meaning hits home.
For example, email marketing service AWeber ran a simple copy test on their call to action.
The only change? A single word.
AWeber added the word “Now” to their call to action. And they saw a 12% increase in paid signups with a credit card.
An online travel booking flow is no different than any other conversion flow. Doesn’t matter if we’re talking about signing up for a new email marketing app or trying to go through a shopping cart checkout sequence.
The stats are remarkably the same, too. Online travel bookings see a 81% abandonment! While shopping cart abandonment averages right around 70%.
61% of those cart abandonments are because of ‘extra costs’ (including shipping, taxes, fees, etc.)
You know how this feels. You’re super pumped about that new pair of plastic jeans (yes, that’s a thing) you just found. Except when you head over to checkout, you see that another ~30% has been tacked on due to taxes, shipping, and fees.
Guess what Expedia does, instead?
First, they ‘drop’ the price. Two cents. Literally. But it’s green and happy and there’s a check mark exclaiming “Good News.”
The other thing it says? “Book now to secure this price.”
Zooming into the pricing area on the right, you also see the savings of booking the flight and hotel together. Then, down below, you see the total price (again first – price anchoring).
And then a “Due at hotel” line item that cleverly buries all of those damn resort fees that we hate so much.
But they’re almost invisible because of how Expedia has positioned this pricing and sale.
Instead of being ‘thrown off’ the conversion scent at the moment of truth, you’re practically already packing your bags. #Humblebragging about your upcoming Vegas trip.
Conclusion
Ranchers use a cattle prod to get those big, dumb, slow moving animals to do what they want.
Whether that’s to eat, find shelter, or head to the slaughterhouse.
Consumers don’t need to do anything.
They might want lots of things. But they lack nothing. And so there’s no inherent desire to purchase your widget.
Instead, you have to create it. Manufacture it and bring it into existence.
For guidance, start with the web’s top converters. Expedia is a master at creating urgency by using countdown timers, product attributes, prince anchoring, FOMO, and a host of other psychological tactics that would make Cialdini proud.
Increasing conversions online isn’t about tricks or gimmicks or hacks. It’s about building up the value of your offering so much that people can’t help but convert.
About the Author: Brad Smith the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.
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10 experts advise how to powerfully pair growth marketing with SaaS product development
Contributor Ben Jacobson taps 10 software gurus to reveal how SaaS marketers can bake marketing right into their products.
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Why your explainer video matters to your B2B customers
Explainer videos are an essential asset for B2B marketers. Columnist Alexander Kesler shares tips for crafting powerful explainer videos that will bring your brand higher conversions.
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Writers: An Opportunity to Get Copyblogger Certified
This one is just for the professional writers in the audience.
You may have seen that we have a listing of recommended Copyblogger Certified Content Marketers. I’m going to tell you a bit about who those folks are and how they’re selected.
If you want to hire an excellent professional writer who understands content strategy, that’s where you look for one.
And if you’d like to join that group of recommended writers, this is how you can apply.
What’s in the program
Certification has three main components:
Education
The Certification program starts with a four-week online course taught by me and Brian Clark. It’s designed to take you from being an excellent writer to being an excellent writer who can implement content strategy.
“The Certification program pulled it all together for me. It was truly my aha moment — I got it! Not to be melodramatic, but all the components of content marketing aligned for me.” – Mark Crosling
Note: This isn’t a writing course. If you don’t come into the program with solid writing skills, you won’t leave with them, either. We may do a writing course at some point (I’d like to), but that day is not today.
The course will show you how to think about content strategy at a professional level. It includes workbooks and checklists you can bring with you to client meetings, so you can nail down the hard questions (and look incredibly smart and prepared) before you write a single line for your clients.
Once you’ve completed the course, you’re eligible to submit your work and apply for Certification.
Application
Not everyone who completes the course becomes Certified.
Every application is closely reviewed by someone on our writing team. We’re looking for excellent writing, professional presentation, and a demonstration of solid content strategy. If your application shows us a writer we’d be proud to recommend, you’ll be Certified.
Every evaluation includes a detailed critique. So if there’s a fixable problem, you’ll know what the specific issue is and how to correct it … and you can re-apply.
For me, this individual application process is at the heart of what makes Certification valuable. You’re not showing that you could pass a multiple-choice quiz — you’ve shown work that demonstrates, to a fellow professional writer, that you’re a pro with solid skills.
Ongoing education
The program also includes membership in our Authority community of content marketers. That’s where you’ll get ongoing education for your Certification, including sessions on traffic strategies, evolving content best practices, and insights into how to run a more profitable business.
You can even apply for an in-depth mastermind-style “hot seat,” where we take a close look at your business and help you develop a plan for how to reach your next goals.
“The other thing about the program that’s great is the invaluable support and information you get during and AFTER you’ve completed it. Being in the Authority program gives me access to awesome continuing education. Worth every penny — and the listing on the site has really gotten me a ton of work.” – Trudy Roth
What it’s doing for our writers
Making a living as a writer isn’t easy. Finding new clients, managing your business as a business, positioning yourself to rise above the pennies-per-word freelance treadmill.
The Certification program exists to reward good writers with more clients, more revenue, more stability, and more respect.
“The education Rainmaker Digital provides through Authority and the Content Marketing Certification program has helped me further advance my freelance writing career, and the result has been an increase in the quantity and quality of client inquiries.” – Kristi Hines
We also, of course, reap the benefits of having a highly qualified group of professional writers we can point to when businesses tell us, “We’re sold on content strategy, but we can’t find anyone who can implement it well.”
What you should do next
- If you’re a writer and you want to turn yourself into a valued content strategist
- If you’re a writer and you want support and advice on reaching your professional goals
- If you’re a writer and you want to find better clients and belong to a prestigious list of recommended writers
… then you want to join us and get Certified.
Take your writing business to the next level with our Certified Content Marketer training
If you’re interested in becoming a Certified Content Marketer, add your email address to our waiting list below to be the first to hear when the program reopens.
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15 Inspiring & Actionable Social Media Marketing Tips for the Modern Marketer
After years of using “fuzzy math” to calculate the value of social media marketing, marketers are being tasked with generating and showing true ROI. But the truth is, ROI isn’t always just about revenue.
Depending on brand objectives, social media ROI could mean everything from awareness and social engagement to visitors to the company website from social media platforms.
If you really want to make social media marketing a major part of an integrated and omnichannel digital marketing strategy, use the tips below to lead your way.
Know What You Want to Accomplish
Without a clear strategy in place, tools won’t make any difference to you. @IanCleary
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Set goals. As with any digital marketing tactic, knowing what you want to accomplish before you start will help guide your way.
Document your strategy. Taking the effort to document your approach will help you weed out useless activities that will not impact your goals.
Understand when to adapt. Social media platforms quickly evolve. And as the algorithms and user behaviors change, so should your approach.
Focus on Building Real Connections
Social media is not just a business experience, it’s an emotional experience. @MariSmith
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Take an interest. In order to connect with your audience, you have to understand who they are. Take an interest in who they are, what they care about and who influences them.
Encourage interactions. Strive to entice your social media audience to interact with your brand and with each other. The more conversation that happens back and forth, the more connected they’ll feel. Also, many platforms allow for polls, voting and other opportunities for interactivity. Test on your audience and see which ones they respond to.
Speak human. All too often, brands take on a much too formal tone for social media. And while you want to maintain your brand identity, social media followers expect you to lighten the tone.
Be responsive. Social media has created an always-on opportunity, and expectation. If you don’t have a large team that can monitor interactions 24/7, be as responsive as is reasonable for your team.
Arm Yourself with the Right Tools
Content is fire, social media is gasoline. @JayBaer
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Monitoring tools. Many tools exist on the market today that can measure brand mentions, sentiment and more which can help you identify areas of success and opportunity.
Scheduling tools. While what you post is most important, knowing when to post can also have a great impact. Find tools that have an auto-publish feature that is based on the most optimal times to publish social content.
Curation tools. Proper content creation is an essential part of any social media marketing program. Curated content allows you to offer valuable content to your audience without only serving up your own information.
All-in-one tools. Many paid tools on the market can help you accomplish all of the items above (and so much more) for a reasonable monthly fee. If you’re looking for a new tool, see if there are free trials available so you can try before you buy.
General Tips & Best Practices
Social media replaces nothing, but compliments everything. @NealSchaffer
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Consider giving live video a shot. It can be intimidating, but consider opening up and testing live video. Interviews are a great place to start because they don’t require scripting or as much practice to create interesting videos.
Embed videos natively. When you shoot videos to use in your marketing and are ready to promote, upload videos natively to social media marketing platforms. That will encourage more engagement (due to autoplay) in a format that doesn’t require your audience to click or leave the platform to interact.
Use visuals. Social media marketing messages that include visuals are much more likely to catch and keep the attention of your audience.
Understand where paid social fits in. As it becomes increasingly competitive to gain the attention of your online audience, social media platforms are requiring more and more that brands invest in paid social. Don’t fight it but be mindful of where you invest.
What Next?
While some of these tips may not be new, it’s good to remind yourself why you’re incorporating social media into your digital marketing strategy and some simple tips to keep you on track.
If you’re a social media marketer, what have you found to be the most successful and least successful ways to reach your goals?
TopRank® Online Marketing Newsletter.
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Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?
Hollywood paints a grim picture of a future populated by intelligent machines. Terminator, 2001: A Space Odyssey, The Matrix and countless other films show us that machines are angry, they’re evil and — if given the opportunity — they will not hesitate to overthrow the human race.
Films like these serve as cautionary tales about what could happen if machines gain consciousness (or some semblance of). But in order for that to happen humans need to teach machines to think for themselves. This may sound like science fiction but it’s an actual discipline known as machine learning.
The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.
Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.
For digital marketers, machine learning may be especially helpful in getting products or services in front of the right prospects, rather than blanket-marketing to everyone and adding to the constant noise that is modern advertising. Machine learning will also be key to predicting customer churn and attribution: two thorns in many digital marketers’ sides.
Despite machine learning’s positive impact on the digital marketing field, there are questions about job security and ethics that cannot be swept under the rug. Will marketing become so automated that professional marketers become obsolete? Is there potential for machine learning systems to do harm, whether by targeting vulnerable prospects or manipulating people’s emotions?
These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.
What is Machine Learning?
Machine learning is a complicated subject, involving advanced math, code and overwhelming amounts of data. Luckily, Tommy Levi, Director of Data Science at Unbounce, has a PhD in Theoretical Physics. He distills machine learning down to its simplest definition:
You can think of machine learning as using a computer or mathematics to make predictions or see patterns in data. At the end of the day, you’re really just trying to either predict something or see patterns, and then you’re just using the fact that a computer is really fast at calculating.
You may not know it, but you likely interact with machine learning systems on a daily basis. Have you ever been sucked into a Netflix wormhole prompted by recommended titles? Or used Facebook’s facial recognition tool when uploading and tagging an image? These are both examples of machine learning in action. They use the data you input (by rating shows, tagging friends, etc.) to produce better and more accurate suggestions over time.
Other examples of machine learning include spell check, spam filtering… even internet dating — yes, machine learning has made its way into the love lives of many, matching up singles using complicated algorithms that take into consideration personality traits and interests.
Machine learning may be helpful in getting products or services in front of the right prospects.
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How Machine Learning Works
While it may seem like witchcraft to the layperson, running in the background of every machine learning system we encounter is a human-built machine that would have gone through countless iterations to develop.
Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.
So how exactly does machine learning work? Spoiler alert: it’s complicated. So without going into too much detail, here’s an introduction to machine learning, starting with the two basic techniques.
Supervised learning
Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.
Gmail’s spam filter is a great example of this. When you label incoming mail as either spam or not spam, you’re not only cleaning up your inbox, you’re also training Gmail’s filter (a machine learning system) to identify what you consider to be spam (or not spam) in the future.
Unsupervised learning
Unsupervised learning systems use unlabeled incoming data, which is then organized into clusters based on similarities and differences in the data. Whereas supervised learning relies upon environmental feedback, unsupervised learning has no environmental feedback. Instead, data scientists will often use a reward/punishment system to indicate success or failure.
According to Tommy, this type of machine learning can be likened to the relationship between a parent and a young child. When a child does something positive they’re rewarded. Likewise, when “[a machine] gets it right — like it makes a good prediction — you kind of give it a little pat on the back and you say good job.”
Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.
The Power of Machine Learning
A lot of what machine learning can do is yet to be explored, but the main benefit is its ability to wade through and sort data far more quickly and efficiently than any human could, no matter how clever.
Tommy is currently experimenting with an unsupervised learning system that clusters landing pages with similar features. Whereas one person could go through a few hundred pages in a day, this model can run through 300,000 pages in 20 minutes.
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The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:
To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.
For some marketers, this raises a troubling question: If machine learning systems solve problems by finding patterns that we can’t see, does this mean that marketers should be worried about job security?
The answer is more nuanced than a simple yes or no.
Machine Learning and the Digital Marketer
As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.
This process usually involves hours of digging through analytics, collecting data points from marketing campaigns that span several months. And while focusing on data analysis and post-mortems is incredibly valuable, doing so takes a significant amount of time and resources away from future marketing initiatives.
As advancements in technology scale exponentially, the divide between teams that do and those that don’t will become more apparent. Those that don’t evolve will stumble and those that embrace data will grow — this is where machine learning can help.
Marketers that don’t embrace data will fumble. Those that do will grow — ML can help.
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That being said, machine learning isn’t something digital marketers can implement themselves after reading a quick tutorial. It’s more comparable to having a Ferrari in your driveway when you don’t know how to drive standard… or maybe you can’t even drive at all.
Until the day when implementing a machine learning system is just a YouTube video away, digital marketers could benefit from keeping a close eye on the companies that are incorporating machine learning into their products, and assessing whether they can help with their department’s pain points.
So how are marketers currently implementing machine learning to make decisions based on data rather than gut instinct? There are many niches in marketing that are becoming more automated. Here are a few that stand out.
Lead scoring and machine learning
Lead scoring is a system that allows marketers to gauge whether a prospect is a qualified lead and thus worth pursuing. Once marketing and sales teams agree on the definition of a “qualified lead,” they can begin assigning values to different qualified lead indicators, such as job title, company size and even interaction with specific content.
These indicators paint a more holistic picture of a lead’s level of interest, beyond just a form submission typically associated with lead generation content like ebooks. And automating lead scoring takes the pressure off marketers having to qualify prospects via long forms, freeing them up to work on other marketing initiatives.
Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.
Content marketing and copywriting
Machine learning models can analyze data points beyond just numbers — including words on your website, landing page or PPC ads. Machine learning systems can find patterns in language and detect words that elicit the most clicks or engagement.
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But can a machine write persuasive copy? Maybe, actually.
A New York-based startup called Persado offers a “cognitive content platform” that uses math, data, natural language processing, emotional language data and machine learning systems to serve the best copy and images to spur prospects into action. It does this by analyzing all the language data each client has ever interacted with and serving future prospects with the best possible words or phrases. An A/B test could never achieve this at the same scale.
Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.
Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.
Recently Unbounce’s Director of Campaign Strategy, Corey Dilley, sent an email to our customers. It had no sales pitch, no call to action button. It was just Corey reaching out and saying, “Hey.”
Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!
Sometimes it’s actions — like clicks and conversions — you want to elicit from customers. Other times the goal is to build rapport. In some cases we should let the machines do the work, but it’s up to the humans to keep the content, well, human.
There is no replacement for personalized content and an honest ask from one human to another.
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Machine learning for churn prediction
In the SaaS industry, churn is a measure of the percentage of customers who cancel their recurring revenue subscriptions. According to Tommy, churn tells a story about “how your customers behave and feel. It’s giving a voice to the customers that we don’t have time or the ability to talk to.”
Self-reporting methods such as polls and surveys are another good way to give a voice to these customers. But they’re not always scalable — large data sets can be hard for humans to analyze and derive meaning from.
Self-reporting methods can also skew your results. Tommy explains:
The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.
Machine learning systems, on the other hand, can digest a larger number of data points, and with far less bias. Ideally the data is going to reveal what marketing efforts are working, thus leading to reduced churn and helping to move customers down the funnel.
This is highly relevant for SaaS companies, whose customers often sign up for trials before purchasing the product. Once someone starts a trial, the marketing department will start sending them content in order to nurture them into adopting the service and become engaged.
Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.
Ethical Implications of Machine Learning in Marketing
We hinted at the ethical implications of machine learning in marketing, but it deserves its own discussion (heck, it deserves its own book). The truth is, machine learning systems have the potential to cause legitimate harm.
According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:
Where we are really going to run into ethical issues is with extreme personalization. We’re going to teach machines how to be the ultimate salespeople, and they’re not going to care about whether you have a compulsive personality… They’re just going to care about success.
This could mean targeting someone in rehab with alcohol ads, or someone with a gambling problem with a trip to Las Vegas. The machine learning system will make the correlation, based on the person’s internet activity, and it’s going to exploit that.
Another dilemma we run into is with marketing aimed at affecting people’s emotions. Sure copywriters often tap into emotions in order to get a desired response, but there’s a fine line between making people feel things and emotional manipulation, as Facebook discovered in an infamous experiment.
If you aren’t familiar with the experiment, here’s the abridged version: Facebook researchers adapted word count software to manipulate the News Feeds of 689,003 users to determine whether their emotional state could be altered if they saw fewer positive posts or fewer negative posts in their feeds.
Posts were deemed either positive or negative if they contained at least one positive or negative word. Because researchers never saw the status updates (the machine learning system did the filtering) technically it fell within Facebook’s Data Use Policy.
However, public reaction to the Facebook experiment was generally pretty scathing. While some came to the defense of Facebook, many criticized the company for breaching ethical guidelines for informed consent.
In the end, Facebook admitted they could have done better. And one good thing did come out of the experiment: It now serves as a benchmark for when machine learning goes too far, and as a reminder for marketers to continually gut-check themselves.
For Carl, it comes down to intent:
If I’m Facebook, I might be worried that if we don’t do anything about the pacing and style of content, and we’re inadvertently presenting content that could be reacted to negatively, especially to vulnerable people, then we would want to actively understand that mechanism and do something about it.
While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.
The Human Side of Machine Learning
Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.
“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:
Computers are still not creative. They can’t think on their own, and they generally can’t delight you very much. We are going to get to a point where you could probably generate highly personal onboarding content by a machine. But it [will have] no soul.
That’s where the human aspect comes in. With creativity and wordsmithing. With live customer support. Heck, it takes some pretty creative data people to come up with an algorithm that recognizes faces with 98% accuracy.
Imagine a world where rather than getting 15 spam emails a day, you get just one with exactly the content you would otherwise be searching for — content written by a human, but served to you by a machine learning system.
While pop culture may say otherwise, the future of marketing isn’t about humans (or rather, marketers) versus machines. It’s about marketers using machines to get amazing results — for their customers and their company.
Machine learning systems may have an edge when it comes to data sorting, but they’re missing many of the things that make exceptional marketing experiences: empathy, compassion and a true understanding of the human experience.
Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.
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