Hi there! I'm fundraising with the fine people at The Lumery to raise $10,000 for Movember, the leading men's health charity. This year I'm doing things a little bit differently. I'm committing to writing at least 200 words per day reflecting on marketing, technology and customer experience for the 30 days of November.
You can check out my team here: https://au.movember.com/team/2339502
And give to Movember here: https://au.movember.com/mospace/13977857
30/30 - Research-driven marketing
Why do so many marketers say they are "data-driven"?
The concept is very popular among marketers and agencies, but it's shrouded in mystery and confusion.
It's almost like being "data-driven" has become some kind of virtue signal to say that you make good decisions in business and marketing, you listen to your customers and you act on facts. Don’t get me wrong, these are all good and helpful things when creating strategies and determining results.
But I'd argue that the concept of being “data-driven” is about ¼ of what it means to make good decisions in marketing. And if you base all decisions and ideas around data along you won’t get far. Research-driven might be a better way to explain what it means to make good data-informed decisions (or it could just be another buzzword, it's worth a shot).
Data analysis is about determining causality or correlation to explain what is happening with your customers. It could take the form of pinpointing the areas of the customer journey that need attention, forecasting revenue opportunities, analyzing test results, calculating churn, or lifetime value. These activities give marketers clarity on what the team needs to work on, and more importantly, what decisions you need to make.
But it’s not enough, there are other aspects to being data-driven that are incredibly important when it comes to making decisions. Marketers need to consider what your customers say about their experience (explicit insight) by interviewing them, asking them to try your product, and offer opportunities to give feedback. Most hard data analysis is implicit, monitoring the behaviors of customers, but it’s important to qualify your assumptions by speaking to customers directly.
Another factor is market change and seasonality. By monitoring the trends in the market, what the most influential people in your industry are saying, or fluctuations in seasons and/or major events adds a necessary layer of context to your decision-making process. Are marketers able to rely on data collected this year throughout a pandemic, when conditions are extremely abnormal? Probably not. Understanding market change is the foundation that brilliant ideas are built on.
Sometimes ideas and decisions don’t rely only on customer data but on brand perception. At certain points, marketers just need to take risks and try new things, even if it goes against what the data is telling you, within reason of course. But this is where new ground can be made up and how brands can look to differentiate - by taking novel ideas and experimenting with them. Being data-driven can dull these instincts at times and hold back new ways to engage customers.
So instead of being data-driven, let's be research-driven because it's when you take a holistic view to understanding and acting on what you learn about your customers.
29/30 - Cultivating soil on rented land. The rewards of social media.
The other night I read my daughter a bedtime story. The three little pigs. It's a classic children's story with some ancient wisdom - when you build a house with materials that don't last, it can easily fall over.
The same is true of social media. There are millions of people on the internet working hard to build their social media audiences, with some people turning overnight into millionaires and influential figures. Most of us are lucky to get 1,000 people to view our post.
The thing with social media is that whenever you are posting, you are contributing to someone else's business model. You don't own the house - Facebook, Twitter, LinkedIn and TikTok own it, but they need you to contribute so the house becomes more valuable.
And so we post daily, create great content, add value, comment, like, share and retweet to build a following over time. It's a lot of effort to go from 0 Twitter followers to 100. And a lot of that effort results in audience that can be removed at any time whenever the landlord wants to change things up. We've seen this recently in Facebook's 2018 change of the newsfeed algorithm and LinkedIn's update of the feed to prioritize connections. You may be working hard for your brand to build a social following, but you still need to adhere to the rule-makers to hold onto that audience.
That's why it's kind of like building a garden on rented property. You can enjoy it's produce this summer harvest, but it will be unknown if you can reap what you sow next harvest because your landowner can change the rules, evict without warning or raise the rents.
Now, I'm not saying social media is evil, or that it doesn't have a place in a marketing strategy. I'm saying that social media should be paralleled to television media and out of home media. Followers should not matter as much as getting people to visit your website, make a purchase, join a list or make a donation, because that's what a channel is - it gets your customers out of one (unknown) environment you don't own to one that you do.
28/30 - The data <> insight supply chain
Insights don't happen on their own.
No one looks at a computer monitor filled with visualizations, cells, and data and says "I have an insight!"
Great insights happen through a process. There's a supply chain to it.
A long time ago I took a job as a coffee delivery person (yes, I did drink way too many lattes in the job). One of my responsibilities was to ensure that the warehouse had the stock flowing properly. Old products out first, new products at the back of the warehouse.
With data and insights, it's a lot like managing a warehouse and making deliveries. There are phases to data analysis that are unique to the work.
Things like writing the research brief, collecting the data, normalizing and standardising the data, analysing the data, visualising the data, presenting the data, socialising the data, producing documents showing the data, and finally closing it all down.
Every company has some different kind of process similar to the above, but what does the transformation of data (rows in a spreadsheet for example) to insights (key things someone has learned, a revelation, a problem, an opportunity) look like as a process?
It's about as messy as any kind of creative task. Insights can jump out at you at any moment when you're going through the data analysis. You might go through analysing data for a week and find nothing. Like panhandling, searching for golden nuggets in the stream can take hours, days or years.
Might I suggest a supply chain process that has worked for me:
Phase one: Exploration. The phase in which you open-endedly explore the data, figure out your dimensions, play with visualizations and determine what is important in your data set. There should be no deliverable work. In this phase it's really about burning time figuring out the data you want to focus on.
Phase two: Analysis. This is the phase in which you start honing in on a few key areas you want to focus your analysis on. It could be a list of things you find in phase one, or a list that was briefed into you. In this phase, the focus is to really do the hard lifting of analysis to start deriving insights and learning.
Phase three: Challenge. By now you should have some kind of early formation of insight, either in data visualisations, scribbles or paragraphs written. These are the key things you've found in the data that will form your recommendations and visualisations. Now it's time to bounce the insights around, ask yourself - why are these insights important? Are there alternative reasons for what caused these insights in the first place? Am I assuming anything about the data? The challenge phase is best served with a generous dose of colleagues who have no context or understanding of your project.
Phase four: Write. You should have some refined insights by now, things that have been through the process of being challenged and hopefully, you have quite a few less. Now it's time to get the data, visualisations and learnings on a page. The format doesn't matter because it's about getting the thinking down on the page and your main insights and learnings.
Phase Five: Story. The last step is to take what's on the page and editorialize it into a structured story, including an executive summary, key talking points, and supporting analysis and visualisation. The best analysis reports have one big idea per page. Everything you did in phase four lives mostly in an appendix.
Just like delivering coffees from a van and managing a warehouse, there are phases that coffee beans have to go through before they get to the customer's coffee cup. Data is no different.
27/30 - Social media in 2035
I picked 2035 purely at random. It's far enough in the future to be completely mysterious but feels close enough to relate to today (for example, we had cars in 1910).
Now that the genie is well and truly out of the bottle, social media technology is diversifying out of homogeneity (Twitter has diversified into Gab and Parler, Instagram has been diversified out into snapchat and TikTok).
The central question is what networking the entire world will do to society.
Not too long ago, people received their information locally and in gated and centralised formats (like newspapers, churches, bulletin boards). The invention of the printing press made it possible to scale and distribute information like never before, turning local enterprises into national organisations. With the advent of television, all of a sudden real time news went statewide, national, and global. Now with social media, we've seen the fracturing of centuries-old news institutions because the news feed of the people is built by the people to serve the people.
Gone are the days of centralised and gated content. Everyone is now an editor and everyone is now an arbiter of what's real or fake.
If Moore's law is anything to go by, the technology will go beyond anything we've seen to date. We're only about 30 years proper into the internet experiment. In that time the change has been so rapid, and so profoundly unrecognisable from just 10 years ago that it's hard to predict even just to 2030.
Here are a few considerations for what social media could look like in 2035.
Generational media: We are recording all of our memories into the cloud, and so things like genealogies will become much easier. We will be able to pull up what our great grandmother was doing at a precise date and time and hopefully we will be able to learn from our mistakes in history. We will also have complete generations that are integrated into digital channels from childhood to old age, spanning the entire lifetime, so you'd make the argument that age data will be the gold standard for advertisers.
Centralise and decentralise: I believe the next 20 years or so will be a phase in which social media moves away from big tech oligarchies to smaller social media units fitted out for particular religious, political and interest-based groups. But then we'll see a centralising again when people get tired of managing multiple platforms. We'll see a number of iterations on this over time.
Government regulation: Like any society impacting industry like tobacco, oil, automation or aviation, social media will become a regulated industry. So much so that by 2035 it will just be normal to have government oversight applied to how algorithms (or the future equivalent) will be constructed, engagement rules and probably even sticker warnings on what social media does to your brain. If the 2016 election is anything to go by, in 30 years from now the impact of social media will only become even more significant to the public discourse.
Institutionalized News: News authorities will still be the most reliable places of information. If this is augmented or integrated into technology business models, that's up for debate. But editorial and journalistic oversight, fact checking and data analysis will continue to be extremely valuable a century from now, mostly because people need reliable facts.
The marketplace: Social media has the opportunity to replace the internet as we know it. For Facebook, some third world countries see no difference between the social platform and the open internet. What we're seeing today are proto-digital marketplaces represented by the social media platforms. It's an early work with alot of bugs, issues and mistakes. But that's the point. We'll probably see that social media will lose the term already and just become the default OS of human interactions and experiences.
At the end of the day, we all don't know where it will go. But one thing we can know for sure is that social media is taking humanity somewhere new.
26/30 - Distraction and engagement
This week I got a Black Friday email that looked like it was erroneously sent, but it was a clear tactic to drive up engagement.
The actual email message was below a reply all by the CEO of the company, saying to his team "make sure you check all the links before we send this one out."
Perplexed as to why any brand would want to do something like this, I reached out to the CEO on Twitter. His response was to reference copywriters who have done something similar, taking an out of the box approach to engagement.
I applaud them for thinking creatively about email marketing, but the only problem was that I was so distracted by their tactic that I didn't even bother to read their Black Friday offer! I was way too curious to find out if the mistaken send was a real mistake or a deliberate tactic to drive more email opens and clicks.
These days a lot of brands are trying to "engagement hack" their audiences, but in most cases, you can probably tell that if a marketing team is relying on hacks like these, they don't have a product that can speak for itself.
The core job of any marketer, designer or copywriter is to make the value proposition clear, compelling, and relatable. That's it. That's your job. Anything else is a distraction for you, a distraction for your customers and a distraction in the marketplace.
25/30 - Product vs Marketing
Product has become to marketing what sales was to marketing ten years ago. What I mean is as companies have matured digitally, more consumers are deciding their own purchasing journeys with less reliance on sales and more reliance on technology and products.
We're now in an age where product and marketing teams need to work closer than ever to get results and create customer experiences that matter.
But here's the catch, companies tend to fall on either marketing or product when it comes to where the growth focus is and rightly so.
Some companies are not product driven, because their products don't change much. When was the last time you saw innovation in something like crockery? A bowl is a bowl and has been that way forever, but the companies behind crockery need to sell product and rely on marketing to stimulate demand and push the product in the market place. So it's fairly obvious that when it comes to who gets a say, the marketing team should probably be the ones to determine how a company growns.
This is not the way with product lead brands. Mostly because companies that are building software or are contasntly innovating in hardware or have a majority share in revenue from digital channels should be constantly evolving their products to solve customer problems. And because product teams have such high involvement in the customer's experience and the growth of a company, marketing has to play a different role. If you have a product company that is driven primarily by marketing, you may be able to drive revenue, but without product teams having a significant say in the direction of products and marketing too, you end up with short term growth and customers who evenually leave for someone else.
Product and marketing teams should work hand in hand. And when they do work hand in hand what you see is great, innovative and important products and innovations heading into the marketplace with the support of marketing teams to help cusotmer's understand why the product team's work is important to them.
In product lead companies, marketing plays a significant role in elevating what product teams are doing, but it's product that creates opportunities for growth.
25/30 - The Rashomon effect
Rashomon is a Japanese movie in which a number of people tell their own version of the story a Samurai's murder. The stories told are slightly different in how the events transpired but all of the stories explain the outcome similarly enough that all of them are true.
The Rashomon effect is a helpful mental model to explain how machine learning can be improved over time. Especially as it applies to understanding the impact of a number of different data points can have for things like product recommendations or pricing personalisation.
It's a way to conceptualise the way a machine learning algorithm works by changing the variables that produce the output, not the end user experience.
By breaking things down into each rational explanation for why the model changed based on small tweaks in the data (such as introducing a new data point, or having to much of the same kind of variables), then you have everything you need to start eliminating the reasons for why the machine learning model is making a certain prediction.
The Rashomon effect is a great starting point for going through the process of elimination to understand what and why something caused a change in an algorithm. But it's also good as a principle for data analysis as well.
We should be taking a Rashomon approach when doing our analysis. It's hard work but you get to a better outcome when you challenge yourself with counter factual and alternative explanations for the insights that you find. Even better is to throw you analysis to your team or a few colleagues and ask them - how would you explain what's behind this insight?
When you do the Rashomon effect, you end up with better answers to your questions and more clarity on your insights.
24/30 - The ethical marketer
How many people graduating university this year with marketing degrees have some form of training in ethics?
When was the last online marketing course that also included a module in digital ethics?
What companies are providing onsite training on building an ethical marketing practice?
The short answer to these questions is very little if ever at all. It's rare to meet a marketer well versed in the principles of consumer ethics. But it's more important than ever.
The last ten years has seen marketers handle and manage private data about their customers, control the flows of information, create strategies to exponentially scale their messages and create highly personalised content at a one to one level.
And that's just the tip of the iceburg when it comes to the hundreds of decisions made every week that marketers need to make, impacting their co workers, customers, media and at times even society. Never have we lived in an age where data and technology can have so much of an influence over individual's life.
It's also compounded by the commercial and political incentives that exist within many organisations. Marketers exist to grow companies, contribute to the bottom line and make customers do things that translate into net positive outcomes for brands. Some of the best marketers balance their conscience, a strong understanding of ethics and their ideas to drive more business value. But most tend to fall on the growth side of things over the ethics side, sacrificing the genuineness of a brand for clickbait, urgency timers and cheap heuristic hacks to make customers purchase.
One thing for certain is that what makes brands resilient and able to drive long term value is its people's values and character, including the marketing department.
Now is the best time to invest into basic ethical training. It's this which can set any marketer up for a lifetime of sound judgement.
23/30 - The diversification trap
The temptation to diversify content, product and channel is ever present.
There's always a promise that if you start posting content on TikTok, start a podcast or move into a new product vertical, that it will be fun, exciting and will create new business value.
In reality its more like when our second child, our little baby boy came into our lives. It was exhilarating, and exciting to bring him home. But let me tell you - it's a lot of work and a lot less sleep. Such is the way when you diversify, it's another child you need to clothe and feed, and clean up after.
Every new channel, product or content opportunity can be appealing and exciting, but what tends to happen is that diversification can be a big distraction and a source of technical and strategy debt without a vision for what you want to do.
It's easy to diversify, but it's harder to evaluate opportunities with you guiding strategy and vision. A proper strategy with a deliberate, data backed decisions gives more chance for diversification to succeed.
This is squarely because strategy should ensure consistent effort, real focus and an investment into the future. Without it, diversification becomes a flash in the pan without creating any real true value.
It's ok to be slow to diversify. And it's ok to sit down and think about it first.
22/30 - Shiny things
New technology doesn't solve company problems. People do.
It's hard to find a pitch deck from any SaaS vendor that doesn't have some sort of benefit statement related to how their technology brought in revenue, made people's lives easier or solve some big organisational challenge.
But it's a different picture when it comes to implementing and using the technology.
So why does the cycle between 1. Big promise. 2. Big fail and 3. Another big promise continue ad nauseum in marketing tech?
It's because of our fundamental faith in the ability of technology to solve human problems. Since humanity discovered fire and the wheel, we've been on an endless quest to innovate and improve life through the means of technology.
But there's more to it. Here's a few ways in which people shortcut their thinking when they decide to purchase more tech.
Reducing friction - I can buy this product to solve my problem for m
Genuine excitement - this product is really innovative
Competitiveness - our number #1 competitor uses this product and is successful
As you can see, there's really no big difference between buying tech and buying shoes, we all want something that will make our lives (and companies) better.
If I could offer some small piece of advice it would be this - look at how the people who use the technology will be empowered to utilise the product. Ask questions - on if the value add is clear, does it solve a technological problem in a way that will both save on costs and drive efficiency, and will this tech make sense with the existing skill sets in your team.
Buy tech that makes sense, and go shopping on the weekend for things that don't.
21/30 - WOMO
Word of mouth marketing (WOMO) is the single most important aspect of the customer's experience.
What other customer experience:
- Comes from a trusted source
- Is the #1 way customers make a purchasing decision
- Can be used across the entire buying journey (acquisition, engagement, consideration and conversion)
- Costs next to nothing to produce (some of the time)
- Educates your customers for free
- Turns existing customers into advocates
You see, word of mouth interactions make the marketing world go around because they come from trusted sources - friends, family, professionals and social network. WOMO establishes credibility by linking a trusted person with a trusted product or service. Before the internet came along, it was one of the foundational pillars of marketing strategies, after all Tupperware didn't invest into teaching product specialists how to do a great morning tea for nothing.
It is estimated that word of mouth marketing accouns for about 6 trillion dollars in annual consumer spending per annum around the world. That's a decent chunk of the economy that boils down to a very simple marketing strategy - getting your customers to tell someone else about you.
But not all WOMO is the same. There is a bit of a heirarchy when it comes to how impactful the strategy can be.
At the top of the ladder is direct share, normally in the context of a personal or professional relationship. This type of WOMO happens when someone thinks your product or service can directly help another person, is something to brag about, is something funny, interesting or newsworthy. This is the strongest form of WOMO, but it relies mostly on having a product worth talking about, and that's no easy feat.
At the middle rung is social networking shares. This is the indirect format of word of mouth, which requires little effort from the person sharing and which can have a significant impact on a brand's reach. Take for example when a brand goes viral, people are voting with their views, likes, comments or retweets that whatever the brand is doing is worth their endorsement. However, there is no direct correlation back to the key product or feature most of the time, as in a direct referral. And it also can have nothing do with your brand (like that TikTok video about Fleetwood Mac and Ocean Spray). If direct referral is worth $100 dollars, then a network share is worth $10.
The bottom rung is the referral share. This is when a customer is incentivised to share the product, brand or service with promotions, cash or something else that might be valuable. This is the lowest form of WOMO because there's no intrinsic linkage between the brand's value and the customer's experience of that value. Mind you there can often be a form of brand equity at play with referral marketing as the consumer might have a close affinity with the brand and is comfortable enough to share it. Because the referrer and sometimes the referee are incentivised this is the weakest form of word of mouth, purely because there's no corellation with how good the product is at the end of the day. If a network share is $10, then a referral share is worth $1.
It's still early days when it comes to leveraging word of mouth marketing online. Without a doubt the internet brought two new formats (network and referral), but there's very little direct innovation in the direct share. The advent of social media and messaging services has no doubt accelerated the way in which people promote products and services to each other.
At the end of the day, if your product is not good enough to talk about, then creating viral content or incentivising your users will just become another distraction.
20/30 - Do hard things, tell your customers
I was reflecting this week on how a reputation is built over time. How companies like Toyota, Amazon, Netflix started one day and have become global brands and household names. In the age of the internet this latency between starting and going global has gone from years to days and now to milliseconds.
A few examples on how long it took various brands to go global:
- Toyota took 40 years (1935 - 1975)
- Netflix took 20 years (1997 - 2013)
- TikTok took just 3 years (2017 - 2020)
Looking at some of the world's largest and most innovative companies, one thing stands out in how they built their reputation and used it to scale their business globally.
They do hard things well. And they tell their customers about it, and what it means for them.
Doing hard things well is an underrated quality in a lot of product businesses where the go to is to build a minimum viable type product to validate whether or not customers want it. But in a way a lot of big brands tend to make big bets with something very hard to pull off (manufacturing cars, DVD deliveries to streaming and new social media formats). They go all in and let the market decide their fate. In other words, they do hard things well.
This is why clarity of focus, and focused effort is extremely important, because it allows you to pull something off that's hard and when customers benefit from what you create, they will appreciate how hard it is to do and tell others.
19/30 - Marketing simplicity
There is one opportunity that's a constant in any marketplace, and that's selling simplicity.
Simplicity is the most effective thing to sell, because it's a core way in which people connect with products and services. As the saying goes, a complex product with a simple experience is the ultimate competitive advantage.
The reason why communicating simplistically is important is because it's so hard to do. When you're working on something that's complicated, it requires alot of context and is dependant on what you don't know about your customers.
Someone asked me recently how I explain to someone with no experience in marketing or digital, what a person working in customer experience does, and it was hard, very hard to not rely on other concepts or assumed context to explain something. In other words I failed abysmally.
And that's the trick in marketing and especially copy. You need to convey what's important in a way that someone with no context or assumed prior knowledge can digest and understand.
Simplicity is the reason why the iPhone is so successful, it is simple enough for my 3 year old daughter to pickup and understand, but underneath all of that is some of the most complex technology that has ever existed. Simplicty changes lives, and helps people do the things they want to do and buy the things we're selling. That's why Simplicty is so effective.
18/30 - Taking shots at personalisation
What is your appetite for risk?
It's a central question to answer when it comes to personalisation.
This is because most of the personalisation of products, offers, creative and messages revolve around automating what your customers receive and this means that you really have to take the hand of the wheel and let the machine do it's job.
Personalization is a little like gambling in this way, pull the lever and see what comes back, and then and try and try again. The idea is that the house and the customer should always win.
But what happens when it doesn't? What happens when personalisation is actually detrimental to the customer's experience or even worse, impacting the bottom line?
Every company has some form of appetite to risk. And there are some companies and industries that would be impacted more by a personalization project doesn't come off as you would expect. And so some companies have an advantage because they can take more bad shots, move on and try again.
For example, personalised insurance products may be embarrassing and offensive to customers if it recommends something that customers don't want. That means fewer shots at the goal. Take another company, say product recommendations for a retailer, this is less risk because the products and experience is fundamentally different - people aren't normally put off by product recommendations that are not for them. The differentiator is how personal the information is, and how much it encroaches on a customer's private decisions.
So how can companies take more shots at the ring? It's simple - look for high value opportunities that have medium to low risk factor and start there. The more instances of personalisation that are implemented, the better an algorithm can improve and the more you will learn.
The only way to get better is to take more shots at the ring, more often.
17/30 - We will never know what it's like to be the customer
When I started my marketing career someone gave me some advice that I still think about at least once a week.
The advice was this - as soon as you become a marketer for a company you will instantly forget what it's like to be the customer of a company.
And it's true, like severe amnesia it's very hard to remember what it was like to be a customer withou the knowledge of the ins and outs of the company learned while working there.
It's kinda like learning a language, as soon as you understand the words, it's almost impossible to unlearn them, such is the way of stepping into the shoes of the customers - we've forgotten which shoes belong to the customer to begin with.
Companies bridge this gap in a few ways, by crunching the numbers to determine insights about customer's behaviours and by listening and learning directly from them. Both are great to get some insights into the customer's experience and fill some of that knowledge void, but it's still not enough for us to say "we know what the customer wants!"
The fact of the matter is that we may never know what drives a customer to do a certain thing, because we've forfeited that knowledge when we accepted the job offer.
16/30 - Antipatterns in digital strategies
If you work with a team, in any sized company you have probably have been frustrated that things are not working as they should, and it's mostly because of the behaviours of other people.
This is what's called an antipattern - the concept that the assumptions, behaviours and preferences of people in the team can prevent the ability of meaningful and impactful work to occur.
From working with companies on digital strategies across a number of different verticals and industries, I've started to see a number of strategy antipatterns start to bobble up to the surface. Here's a list of five of them:
- Collective strategy: Strong strategies should only be built by team consensus.
2. Top down isolationism: Input and buy in from wider teams and affected members is not required.
3. Throwing your weight around: The highest paid person or the person with the strongest decisions in the room makes the final say for most things.
4. Focusing on revenue: Every single conversation boils down to "so how are we going to make money by doing this?"
5. Ideas before goals: Coming up with ideas before figuring out what you're trying to achieve with your ideas.
Identifying antipatterns is the first step to addressing them.
15/30 - The most important things can't be measured
Digital marketing is increasingly focused on attribution - figuring out where the money is coming from.
It's one of the most pressing issues for CMOs and marketing leaders and it's also one of the most complex. It's pressing because attribution equals clarity and direction and it's complex because it's hard to measure accurately and difficult to aggregate.
Customer's rarely look at a Facebook ad and purchase right away. Most of the time customers convert from a combination of digital and offline channels, including things we'll never know, like a conversation with a friend.
And here's the thing, in our efforts to figure out where customers and revenue is coming from, we need to realise that the most important customer interactions are likely to never be measured.
For example, I always look at open rates and click through rates when I send out my newsletter. But it always strikes me when someone messages me that they've been helped by the newsletter or that they recommended it to their friends.
These are the interaction I really care about, and which most brands would want to know. This is because the most meaningful interactions are the ones that have the most impact on the customer's life and the life of those around them.
The only way to get information about these interactions is by literally speaking with your customers, and even better if they reach out without prompting to tell you about what they value about your product or brand. Without a doubt, trying to put hard numbers against such interactions often ends up in frustration.
In a world where measurement matters, there are just some things we will never know about our customers and that's ok.
14/30 - Using friction
Here's a simple way to create a strategy to improve the customer's experience by capitalising on the concept friction.
But first, what is friction? Britannica dictionary defines it as:
The force that resists the sliding or rolling of one solid object over another. Frictional forces, such as the traction needed to walk without slipping, may be beneficial, but they also present a great measure of opposition to motion.
In customer experience parlance, friction is an opposing force that reduces the ability for customers to do the things you want them to do.
Friction is everywhere on the internet and we experience it every day.
So what is the strategy?
Here it is:
- Increase friction for things you don't want your customers to focus on
- Reduce friction for the things you want your customers to focus on
That's it. And it's behind what made Jeff Bezos the wealthiest man on the planet.
Amazon invests heavily in the customer experience in almost every product and platform, because they know that the faster they can progress customers through steps, the more likely they are to purchase something.
Cautionary note: It can be tempting to increase friction to the point where you are deterring all negative behaviours. But it does come with a strategy tax (see exhibit A below). With great power comes great responsibility, and with great friction comes condemning customer complaints.
13/30 - Strategy tax
Strategy tax is when a product, marketing or experience decision happens on the basis of increasing business value without consideration of customer value.
It happens all the time.
It's a tax because it costs your user something immediately, and will cost the business something eventually.
It's a strategy because most of the time it is guided by data, insight and is a rational way to drive value.
A few examples:
Exhibit A: Making it excruciatingly hard to cancel a subscription.
Strategy: This will reduce the amount of cancellations
Tax: Customers will hate you forever
Exhibit B: Over promotion of content customer don't want
Strategy: Customer will learn to love it and it will lead to engagement / revenue
Tax: Customers become annoyed and will share their annoyance with their friends
Exhibit C: Deal or offer coupon popups when a customer is about to leave the website
Strategy: It will get customers to purchase
Tax: It will reinforce deal seeking behaviours in customers and they will want more of it
Exhibit D: Countdown timers at checkout
Strategy: It will force customers to convert today
Tax: Customers will regret the choice they were pushed to make and request for a refund
Exhibit E: Price anchoring to higher commitment option
Strategy: It will increase average order value
Tax: Customers will be confused on the best option for them and leave the website
Exhibit F: Copywriting to take advantage of presumed insecurities
Strategy: It works for X competitor, and we want to motivate our customers
Tax: Your customers will grow up and see through it
Exhibit G: Promoting polarising viewpoints to generate engagement
Strategy: It will drive, brand reach, engagement and sales
Tax: Half of your prospects will boycott you
I could go on. The point being that when you don't have the voice of the customer in the decision making process, then you will probably make money, and piss off your customers and eventually your boss when you start losing money.
12/30 - Customer journeys are messy and that's ok
If you ask any marketer out there how they would purchase a product online it would normally go something like this:
I clicked on a social media ad, visited the website, then left and forgot about it. Then my partner reminded that we needed x and I searched the brand and a whole bunch of similar brands and chose something.
When you ask a marketer what their post purchase experience looks like they might say something like this:
I purchased something and I forgot about the brand unless there was a sale or I needed the product again.
Customer journeys can be notorious for creating a false and constrained view of the customer's true experience on the way to purchasing and afterwards. Because the act of defining a bunch of phases and describing how customers move through those phases over simplifies what the true customer experience looks like.
With more than 80% of marketers globally either planning a customer journey or having one already, it's a big part of any company's tool kit for formulating strategy and direction.
And here's the thing, customer journeys are not there to explain every single customer behaviour, in fact far from it, it should communicate the desired journey a brand would like to take a customer on that is in realm of control. Just because people are complicated, irrational and impulsive when they shop, it doesn't mean brands can't plan forward so they can at least anticipate customer's needs and deliver an experience to create value.
Of course, the devil is in the detail when it comes to understanding customer behaviour. But it shouldn't stop us from seeking to understand and and plan for it.
11/30 - The labour of love that is customer experience
Can you answer these three questions?
Why do customers purchase from your brand?
Why do customers open your emails?
Why do customers recommend you to their friends, colleagues and loved ones?
There could be a million answers to these, but you can crudely boil the answer down to this - you're customers enjoy dealing with your brand.
In so much of enterprise level marketing and digital work, the environment can be very erudite; logical, falsifiable and rational; there's data to analyse, tech to figure out, campaigns to send, workshops to attend. In this domain the most logical and rational minds win the day.
And that's a problem, especially when the part of the job of customer experience is to make our customers happy.
Customer experience is a labour of love. I've realised 0ver time that if whatever I'm planning for the customer is not fun, interesting, helpful or enjoyable then I need to re-think it. Because it really boils down to this - if the team is not excited about delivering the experience, then the odds are that the customer is not going to be excited about receiving it too.
The best chef's in the world are intensely passionate about what they do. And that's why people spend thousands of dollars on a single dish.
The best wedding planners strive to create an setting that will give the bride and groom and their guests joy. And that's why the best of the best are always booked out.
The most famous musicians enjoy the process of creating their art. And that's why they sell out stadiums.
Some of the first pieces of advice I received when starting out in marketing was this; every sale is a transfer of enthusiasm. Or in other words, if I'm not excited about it my customer won't be either.
Crafting a customer experience is a labour of love and when you love something, it's fun, enjoyable and rewarding for you and and your customers.
10/30 - Not all negative results have negative outcomes
This week I received my very first unsubscribe from The Martech Weekly newsletter.
I didn't take it well. It's been almost 6 weeks since I started the newsletter but knew that day had to come and it is now here.
Don't worry I did cry (that much).
After talking to a few other marketers about it, one thing that stood out to me was that the other 99% of the mailing haven't unsubscribed, so see it as a sign that one person has thought that it's not for them, but that the vast majority have continued to say it is for them.
Often marketing analysis approaches can be quite binary, did we make revenue? Did we lose subscribers? Did we prevent churn? These approaches have to be this way so we know what to avoid, and what to focus on.
But when we create a black and white dichotomy between positive and negative results we can miss the insights in between. Negative results can lead to some break through ideas and moreover tell us which customers we should avoid acquiring, that's a positive. Conversely a positive result, like increased conversion rates, is a good outcome on the face of it, but is nuanced by the increase in customers returning products.
Next time you're analysing data, ask the question - is there a flip side to what I'm seeing here? Can this negative have positive aspects to it and the other way around?
9/30 - Has technology diminished the role of the marketer?
The world of marketing has changed drastically since 2010 and as someone who entered into this field when the digital takeover was fully underway, I've missed what the old marketing world would have looked like.
As I look around and see the relationship technology undeniably has with marketing, it makes me ask one question - has the adoption of technology made marketers impotent in their jobs?
What I mean is that with most things technology replaces everyday tasks that used to take a lot of effort. Tasks like looking up an address or buying new clothes or sending a message to a friend have all been replaced with digital alternatives. What was once a physical map, retail store and the post office has now become Google maps, Amazon and iMessage. Now as tech has made life a little easier, those tasks that we used to put effort towards have become irrelevant because those skills are not needed anymore.
So how does this apply to marketing? Well in one way marketers have had to skill up in many new ways. From SEO to email marketing to personalisation, marketers around the world have invested wholesale into understanding data and technology to meet their customers needs online. So in a lot of ways marketers have become very skilled. But we're now seeing an age where the amalgamation of technology and it's ability to automate even more of the marketer's everyday workload is almost growing exponentially.
From machine learning powering product recommendations to AI created analytics reports to the ability plug and play entire lifecycle marketing strategies, many tech vendors are looking to minimise the amount it time it takes to get something out into market and create value. And all of these things are great, a boon for marketers and digital people everywhere.
But when marketers start handing the keys to their strategies to technology vendors and ML programs that's when the role of the marketer becomes diminished. Marketers need the passion, they need to empathise with the audience, they need to think deeply about the customer's needs and wants, they need to be able to come up with ideas that sit outside the realm of marketing tech.
Things marketers should be mastering, like creating a strategy, can't be automated, and sadly if strategy is foregone for a more efficient, more cost effective and scalable technology solution then we get either one of two things; one, the bland, sameness of customer experience, with little regard for differentiation or cut through which leads to two, lack of tangible results and forward thinking to drive brands to where they need to be in market. When tech takes over marketing strategy all you have left are people who manage platforms, not people who are coming up with brilliant ideas and finding unique opportunities to create customer and business value.
Marketing and technology is a wonderful blend of art, science and religion. If science takes over, things won't be as fun, or interesting.
8/30 - Person, place and time for ideas
Any marketing idea can be abstracted down to three concepts - People, place and time.
Marketers, strategists and people who are behind the experiences we receive from brands every day can over complicate the frameworks in which ideas are born and results are measured. Not to say that a detailed framework isn't helpful, I'm saying that sometimes a simple approach to marketing strategy can really help with focus.
So let's talk about the three concepts: person, place and time.
Person: Who are you trying to talk to? And what do you want to talk to them about?
Place: Where do you want to talk to them? Do you want to invite them to a place where you can have a conversation?
Time: When is the right time to talk to them? And how often do you want to talk to them?
That's it. So let's break it down into something a little more realistic and TURN Up the marketing jargon:
[Person] I want to target home owners under 30 years old with a personalised message about life insurance. [Place] I want them to see this message mostly on social media and also in our app. [Time] We want to make sure they see the message at the end of the financial year and whenever they express interest in the life insurance product.
Using person, place and time you can articulate the majority of your marketing strategy, without having to go too granular and not having your approach be too high level that it can't be applied to the market.
Sometimes simplicity of approach is a gift to everyone on your team.
7/30 - The hardware and software of customer experience
Most companies are still trying to figure out how to make customer experience initiatives work from an operational front. One thing I've observed is there are different layers of management and teams involved. This means that there are different words being used, different types of work happening and ultimately causes a disconnect.
I like the use the anaology of a computer you have three different pieces of hardware:
The hard drive - The data analytics teams who produce reports insights and analysis
The logic board - The leadership who create vision PowerPoints, ask for money from the board and tell people what to do
The RAM - The marketing team who try and execute customer experience initiatives, come up with ideas
Now if you bought a computer who had all of these essential components they would be more of less useless if they didn't work together.
That's where the software part of the analogy comes into the picture. If your leadership, marketing and data teams can't talk that's because there needs to be an operating system for customer experience. It comes in the form of a framework and a cultural expression that will help everyone talk to each other, orient teams to the common goal and objectives and methodology to get the work done.
This could take the form of agile frameworks, operational structures and other operational ways of doing things. But one of the most important parts of creating software is instilling a culture around customer experience, things that the whole company can be proud of, what teams strive to become and how people treat each other.
Software is how hardware creates it's value and software doesn't live in a PDF but it's the living breathing relationships, methodologies and purpose that brings everyone together to build great experiences for customers.
6/30 - Two types of data analysis
There's two main types of data analysis. Causative and correlative. A lot of people know the difference between the two in theory and a lot of people don't in practice.
For the record:
Correlation: Things that tend to coincide together or have a relationship but don't cause each other. Eg.. Website traffic from Facebook has a low conversion rate.
Causation: Things that that cause each other directly. Eg.. We had a higher conversion rate when we tested a new landing page for Facebook website traffic.
Whenever I see data analysis that relies on surveys or historical data sets, like website behaviour, or customer level data a lot of the time decisions are made with the presumption of causation when what they are really looking at is correlation. Examples of a few insights include customers who use offer coupons have a higher life time value, or customers who sign up online are more likely to churn in the first 30 days. Now these insights may spark action like "let's do more offer coupons!" But in reality we don't really know exactly what causes customers to have a higher life time value because coupons could be one of a thousand individual reasons. So we need to be careful. When it comes to correlative analysis, there is strength in numbers - many correlations can help with understanding a fuller picture of what makes customers do things.
While correlative is more about understanding the relationship between things, causative analysis helps us clearly determine when we can make a decision we can bank on. Causative analysis is the assurance that the decision you will make will be the right one. Normally causative analysis will rule out other correlations to why something is happing, like higher conversion rates from Facebook. One of the most prevalent ways in which causation is established is through AB testing. By testing two versions of things and with statistical significance you can figure out with certainty what changes caused the desired outcome.
I'd argue you need both to have a strong work of analysis, insights you can bank on with context to help you decide.
5/30 - The appeal of artificial intelligence
I think most people working in digital are futurists at heart. We love to think and dream about what the future of technology will bring to our careers, but also how it will impact our customers.
But I'm still not sold on the appeal of artificial intelligence and machine learning as a value proposition to marketers. It's really inescapable now - almost every SaaS platform has some form of AI or ML feature set that tries to make it stand out from the rest.
But will buying a platform which promises to deliver "AI powered personalised experiences for your customers" or "predictive analytics to determine when it's best to talk to your customers" really make my life easier as a marketer and more importantly provide a considerable return on investment?
The school's still out on that. Although people in digital are futurists at heart, they are also attracted to bright, shiny and cool sounding things.
And SaaS vendors are selling these shiny new packaged algorithms as fast as possible. One of the disadvantages of a packaged machine learning products is the most of the time they are pre-trained, and pre-configured for plug and play type scenarios, which is great when you want to get started.
But what can quickly happen is that these programs then become black boxes, with very little intelligence on the way the algorithm is designed to use your data, and even scarier, a lack of visibility on what your customer is actually likely to be exposed to, especially in the realm of product recommendations.
Marketers should have ownership and visibility of their data, and building a ML program from the ground up is a great way to do that. But also is finding programs that allow you to control the data that is fed into the algorithm and gives you the ability to understand the underlying logic of the platform.
Without a doubt AI and ML have some great benefits for marketers and for customers, but as the technology becomes more sophisticated, we too must strive to learn how and why it works the way it does.
4/30 - Deciding together
If your household ever had an family meeting you know how they usually play out. One of your parents gets all the kids together to decide something important, like where you're going to go on holidays this summer. And a screaming match ensues.
In a lot of ways product and marketing teams have a similar "family meeting" dynamic when they come together to decide on things like next year's road map or initiatives to implement as part of a marketing strategy.
A lot of screaming? Talking over each other? Decisions not clearly made? Not everyone bought in? I get it... It's not easy.
There must be a better way.... I call it 360 prioritisation.
There are two ways to get everyone on the same page, and that's to take the subjectivity out of the conversation and celebrate the diversity that exists in the team.
Let's take subjectivity out. Start first by creating a mechanism by which a team can individually score and prioritise the options on the table. Give people time to think, reflect and research before they start putting numbers down. Put numbers against the ideas and show how in aggregate everyone voted. This gives the team a good sense of what's important to the entire team and allows everyone a chance to voice their perspective.
Taking subjectivity out of it allows the team to start by asking "why did we all think this idea was important?" Instead of asking "who thinks this idea is important?" One is productive and the other is limiting perspectives.
As we decide together it's better for everyone if teams celebrate the diversity of thought in the room. Take a typical product team, you have a UX designer, a content producer, a BA, a product manager, an engineer or a data analytics specialist. That's a lot of different perspectives. When we start by taking the subjectivity out first we can then use the numbers to pull apart why someone thinks an idea will be harder or more important than others, and that's where the real good stuff comes out, when a team can create a shared understanding of what and and most importantly why something is important or a lot of effort to execute upon.
So instead of screaming over the top of each other (like my kids do), try a 360 approach to prioritisation, get everyone to share their view and celebrate those views to enrich your next product roadmap.
3/30 - Vanity metrics
As I write this, it's the very last day of the US presidential election with the polls in full swing and the votes coming in. Without a doubt this election will be the most consequential for the country. Can the world really endure four more years of Trump?
The Democratic party has been taking a lot comfort in the polls, showing a consistent 10 points above trump across the nation. But as we all know, we had a similar situation in 2016, showing the world that polls can't always be trusted. A
This, my friends, is a classic vanity metric. Numbers that bring comfort, and numbers that can deceive.
Vanity metrics help you impress upon people that you're doing a good job, that's why they are called "vanity" - it's taking excessive pride in one's own appearance or achievements.
Vanity metrics can't help you determine what you should do from your data analysis. And that's important. Determining what a vanity metric is, is about the application of data, either to appear great or to show you how you could do great things.
Here's another example:
For the first time I think ever one of my LinkedIn posts is about to reach 10,000 people, garnering almost 150 likes.
But to me these metrics are of very low value, other than to pat myself on the back (which is not very helpful and kinda hard). And that's why it's a vanity metric.
The data doesn't tell me anything insightful about my audience.
There is nothing here that I can use to create a strategy or validate what I'm doing.
Most of the people who engaged with the post are outside of my immediate network of those who I want to connect with.
This is because the post was almost a throw away, a random thought and a bit of a rant about Google's design choices.
So it's really just vanity, 10k views sounds great, but in all honesty I'd rather have 10 people that I respect in my industry to thoroughly read my weekly newsletter and give me feedback.
I see a lot of really talented, experienced and accomplished people on social media chase the likes and the views. It's a shame really, especially as I see some deliberately working towards improving some of these metrics.
And so going back to the US election, the real metric is not the polls, it's the vote - people making a deliberate and consequential choice to back either party.
And that's what we want in our data analysis - understanding real customer behaviours that will are consequential for your company. Data you can act on.
Everything else is just looking in the mirror and telling yourself you're pretty.
2/30 - Marketing and meritocracy
You may know of Phil Schiller, the long time serving CMO of Apple. Phil has what many marketers would call an exceptional degree of success in marketing some of the most significant Apple products and has been instrumental in the success at the company. He has a long and storied career filled with success, fame and wealth.
You may also have heard of Elizabeth Holmes, the now failed and bankrupt CEO of Theranos, the now closed blood testing company. Once a company worth billions of dollars, Theranos peddled lies and half truths about the credibility and functionality of their products. And the truth eventually came out.
Holmes is the exact opposite of Schiller.
But it's not effort that sets them apart, it's context.
Holmes learned early on that to get ahead you must fake it until you make it, while Phil committed himself to communicating products honestly and compellingly to deliver real value.
Both worked extremely hard.
Most marketers think that creating value for their company comes in the form of orchestrating campaigns, improving acquisition, reducing churn or delivering great customer experiences. And that's true.
And most marketers will think that it's putting effort behind these activities that will lead to the next promotion, the new pay bump or the next company wide mention.
Therein lies the misleading nature of Meritocracy - the idea that the progression of career has only two dimension - effort and results.
But. Effort and results is two out of three aspects that make up Meritocracy.
We often can get caught in a way of thinking that says - if we can measure and predict what our customers will want and if we act on it and put a lot of effort behind it we'll see results. And those results will be noticed.
Without a doubt, this is a wise way to orient yourself towards a goal. But it's not how meritocracy works.
In reality meritocracy is when effort is applied to a unique context with the mostly unpredictable outcome of results.
Another way to put it:
Context X Effort = ~Results
Marketers can only control one out of the three aspects - effort.
Context is the most important vector to success. It is fundamentally the social, cultural, organisational, educational and personal context that influences everything about the decisions you make as a marketer.
The ideas you have, the amount of education you have received, the people you've met, the way you learned how to write a CV to land your job in marketing, the way you get along or don't get along with people in your team are mostly derived from uncontrollable context factors that have a far larger sway over how successful your marketing career will be and how much merit you will earn on the way up.
So in other words, the success you find in Marketing is mostly dumb luck. But with effort it's a little less dumb.
1/30 - Build credibility through content
I've always been curious about how content can have a drastic leveraging effect on credibility and status on the internet.
If you think about it, content is how people find and engage with your brand, if they are searching, content is the primary vector for how a brand is presented.
People sign up for content, they watch webinars, listen to podcasts, read newsletters. People scroll through social media feeds, read Twitter threads, message each other. All of these examples boil down to a primary method of communication - talking and listening, visualising and transferring. Instilling trust that you know what others need.
Content is how people decide whether or not to buy products, subscribe to a service, register their interest, take out a policy. People who work in data and technology often forget this - that it's the content that counts.
You could be pulling off some seriously cool personalisation strategies, or predicting your customers behaviour, or running hundreds of AB tests per month. And all of that is great, but it can be made better with smart, funny interesting and compelling content. Do yourself a favour and put content further up the list when creating your next strategy and have a chat with you creative team because they are your gateway to the customer's actual experience.