We were joined by industry legend Jay Baer for a live Q&A as we explored the ingredients to data driven marketing excellence.
If you didn't get the chance to watch live, we've got a nice, neat round up of all the biggest and best points.
Plus, if you ask nicely, I'll give a description of his fantastic suit. Okay, it was a dashing grey, black, and white number. Clever red flower on his lapel. Perfection.
Want your marketing to be as data-driven and informed as it can be? Well, you’ll need our State of Data-Driven Marketing 2023 eBook, downloadable here!
So, let's jump into the content. Obviously secondary to the suits, but we'll get into it anyway.
What Does Data Driven Marketing Excellence Look Like?
Technology has allowed marketers to use data in order to provide an experience consumers and customers actually want. This is a type of marketing Jay describes as 'radically relevant'.
All marketers, he says, tell themselves the same lie. They say "oh, my prospective customers are just too busy. They're too busy to come to my webinars, or read the white paper. They're too busy to even flick their eyes to the infographic, or listen to my podcast, or watch this video". And it's a load of rubbish.
"What you're giving them is not relevant to them," he says.
"The antidote to that is, and will always be, specificity and personalisation."
The only way to achieve this additional relevance and specificity is with data. You can't just do it magically. You have to know more about your customer and prospect, and create communication and marketing programmes that feel like they are created just for them.
The Attention Economy is one of the most challenging battlefields in marketing today. So, everything you make has to draw the eye of your target audience.
In this world with so much content is freely available to us, trying to kind of find the things that's worth their time and attention is the difference. And data underpins that, and allows us to unlock and really identifies with consumers, and what is worth their time and effort.
What is The Most Challenging Element To Data Driven Marketing?
Is it the people the process the data, the technology, something else?
It's probably data only because I think largely today, we are surrounded by data but starved for insights
Almost all the marketers in the world have a big old stack of data. They've got either enough data, or are on the way to have enough data. But according to Jay:
Big data is not the goal. The goal is big understanding
So, marketers have to find a way to use all this data that is gathered, held, or analysed by sponsors (among others), and figure out how it can be applied in a way that adds to the customer experience. Remember: data by itself has no value. "It's just a spreadsheet".
You've got to ask: what does the data tell you? What do you actually stop, start, or change in your company as a result of this data?
Sometimes marketers get overwhelmed by the presence of data, and lose site on the need to focus on the application.
"One of the rules that I've had in my consulting business for a long, long time now is never ever, ever create or distribute a report, without a section that says “Here are the behaviour changes that we are instituting as a result of this data.”
You can give someone a report that doesn't have any conclusions, any next steps, and what you're basically doing is chucking them into a world of confusion. They'll look at the data and say, "Okay, cool". "It doesn't have any actual real-world value", says Jay.
"So you got to interpret for people and then say, consequently, we're gonna start doing this or stop doing this or change this."
"If there was a rule there was a rule that we can pass that says that all analytics reports in all organisations can only be one page long, we would be manifestly better off.
We'd be forced to understand what's important and critical and meaningful."
How Can Companies Effectively Transition From Multichannel To Omnichannel?
In a lot of organisations, Jay has seen data, or data lakes, that are not channel agnostic.
So, you have data from all different place. You'll have data from your social programme, you get data from email programme, get data from your web programme, even have separate data from your mobile programme.
Those collections of information are held in a vertical capacity. They don't talk to one another. They don't operate horizontally across the business.
So what I would like to see is when we're working on these kinds of programmes to, instead of creating customer journey maps, to say, “well, what if the customer changes channels?” We should build customer journey maps that assume that all customers are changing.
Then, marketers have to figure out what the minimum data is that they have access to, that can be available on every channel. "Omnichannel data must proceed omnichannel experience."
So, it is vital that your data works across the channels. This is why CDPs are so important; they allow marketers to apply the data in a channel agnostic way, Jay says.
If you don't have the full understanding of what action has taken place across any other channel, silos happen. And this is frustrating to consumers.
Although for enterprise firms, it's not easy to achieve this. With limited resources, this data consistency across all channels is difficult.
But consumers aren't too sympathetic. They'll ask:
"Why do you think I need shoes in this size when I bought shoes this other size, three weeks ago on your website, like they just don't understand."
Which Other Channels Should Marketers be Using?
“I'm putting all my money on telepathy," Jay says.
But on the new, shiny toys in the space Web 3.0 and the Metaverse, he argues that the jury is still out. But it does merit consideration.
However, he wants people to consider the, less flashy, basics. He argues that core messaging apps, Whatsapp, Facebook messenger, continue to be really viable from a customer interaction perspective.
Plus, SMS is also something works, but is underutilised. "SMS for business is still no means a standard, in the US. The pandemic has pushed it on a bit, but there’s still a long way to go."
Jay also points to AI. Conversational AI, and 'wiser-than-ever' live bots have real potential. These technologies save people a lot of time, as opposed to having to phone up, or even send an email. In circumstances when it's bad, however, it's very bad, it's pointless. The tech has come a long way, but it has to be primarily programmed to help customers.
The last example Jay gives is social commerce. The ability to sell goods and service within a social media application, whether on Instagram or TikTok, has only had the surface scratched.
It solves a lot of conversion optimization challenges because the entire system and the entire purchase and data collection happens inside Instagram, for example.
So you never get to the website at all. So, you don't have as many points of failure. I think that's got some potential as well.
This is not an approach for every business, however. You'll not see many people selling legal services or funeral homes on Instagram. But for industries it works in, it works in.
What is The Potential of Direct Mail?
Direct mail has real potential to deliver personalisation for B2B.
Many B2B companies already working on programmatic ABM-drive direct mail campaigns have been interspersing social media ad touches with this highly customised direct mail, in a combined and effective way.
Jay actually started his career in direct mail. "That was my original career as a direct mail specialist way back in the day. And so I'm a huge proponent."
Jay is a fan of "This kind of counter programming...if everything's online, then you do something offline and it stands out correspondingly."
What is The (Ongoing) Potential of QR Codes?
"It was my good friend Scott Stratton wrote a book called Why QR codes kill kittens.
Literally, the whole idea of the book is that QR codes are inherently dumb, and ridiculous and just put the URL there.
And then the pandemic comes and everybody gets rid of menus and restaurants and everything else and all of a sudden it's just like this global resurgence."
QR codes have made a comeback because of the pandemic. They also offer a bridge between the physical and digital, and are able to connect these experiences. So, QR codes have plenty of use cases.
But Jay warns brands against using QRs in an impractical way.
I was on a long cross country driving trip last month. And I saw more than one billboard alongside an interstate with a QR code and I'm like, "Look, nobody, nobody can be driving at that speed, grab their phone and hit the QR code before you go by."
QR codes have huge potential. Everyone has become comfortable with the technology, and most people are familiar now with using QR codes. But, like Jay mentions above, they're not a magic bullet.
But once again: its all about the data. What is the data? What's the orchestration? What's the intelligence of decisioning, the right content, the right creative? The channel is only going to be as good as the things that come before it.
When Does Personalisation Go Too Far?
Everyone has experienced creepy marketing. With the prevalence of third-party data it has become a normal part of everyday life.
However, this creepiness will likely lessen when marketers have to rely on first- and zero-party data. This will be due to the fact there will be a little bit more visibility as individual consumers into how, and where, the data was collected, and by whom.
"Here's what I tried to do. I answer the question two ways. First, in my organisation, I've always used what we call the mom test," Jay says.
"If you're trying to make a business decision, and you're wondering whether your consumers or potential customers will find it inappropriate or creepy just ask yourself, very soberly. 'Would my mother who presumably loves me unconditionally, finds this off-putting?' And if the answer is even remotely, yes, you have the answer."
It's hard to know immediately if your customers have found something 'creepy'. Based on only their click stream, it's almost impossible to understand their reasons. They'll just stop clicking, and you wont know why.
"You almost have to do more qualitative research, survey work, focus groups, etc, to ferret that out. So it can be a little bit hard to measure the creepy factor in a way that is statistically viable."
What Is The Most Impactful Change Marketers Can Make?
Customer attitudes and subsequent behaviours have changed dramatically in the last 2 years, because of the pandemic.
What I keep telling clients is that over the next 18 to 24 months, the businesses that will succeed disproportionately in every category are the businesses understand their customers.
If you're working with personas, customer journey maps, and customer research gathered in the past, it's out of date. Even if the information is from a year ago, customers have changed so rapidly, it's null and void.
This is, again, why CDPs (customer data platforms) are so important. CDPs, data stores, and data lakes, are pulling data based on behaviour, not attitudes gathered from a survey that is no longer valid.
So, customer understanding is the key.
"So, if somebody is looking to really succeed this year, what I would tell them is invest in customer understanding, invest in greater data collection and greater data analysis, invest in survey work, redo your personas, redo your customer journey maps, that entire layer of understanding will be a key to your success."
How Can Marketers Improve Data Driven Marketing Strategy?
Jay gives two words: work backwards.
So often it works the other way round. Marketers will gather the data and then say "what can we make with this?"
It's like buying the Lego set without plans. It just got like a giant box of different sizes and different colours like hey, can I make a crocodile out of this?
Instead, I think the better approach is to work backwards, and say Well, what are we trying to do? How can we create a seamless omnichannel experience? How can we improve conversion rate, how can we improve retention rate how can we reduce call handling time or whatever the circumstances are?
So, it's all about figuring out what the actual objective is first, then moving on to what data is necessary to make that happen.