Drayton Bird recently read a guide to email marketing. He wasn't impressed. In fact, he found it astonishingly bad. A dearth of examples, a torrent of vacuous claims and a scattering of irrelevant imagery. I'm sure you can do better!
Imagine the noble art of marketing as a sporting competition and you quickly understand the need for game changers. Game changers are those exceptional talents who disrupt the flow of the game to make a sudden and decisive contribution.
Companies need game changers too. But it’s not just humans who are capable of making a vital contribution to the success of a business: intelligent technology also has this capacity.
As a senior writer at Lead Monitor – an AI-driven marketing platform by the same company behind such titles as New Statesmen and Press Gazette – I have worked with, and alongside, this technology. I have witnessed first-hand how artificial intelligence, machine learning and propensity modelling all have a vital role to play in “winning” digital marketing.
Everyone’s spending on tech, but they are investing wisely?
We’ve all seen how the adoption of technology within marketing has grown exponentially over the last year. But, even before the vicious pandemic struck, the global marketing technology industry value surpassed US $121bn worldwide, which represented year-on-year growth of more than 22%, according to Statista.
It should come as no surprise that, according to Gartner, 60% of marketing leaders plan to increase spending on technology in 2021, despite budget cuts across industry.
These numbers are all well and good, but if we are obsessed with winning, then surely everyone in marketing is coming to the same conclusion?
Well yes, but the key is in being selective and bold.
In November 2020, we spoke to Abhinav Kumar, who heads up marketing and communications for IT specialists Tata Consultancy Services, about the sheer number of tech solutions available to marketers.
“In terms of using technology inside the marketing function, the sheer number of options available has exploded. Chief Martec, which has been tracking the marketing technology landscape, lists that there are over 8,000 martech solutions available today to marketing departments, up from 3,500 in 2015 and just 150 in 2011.”
Of course a fair amount of these solutions will be very similar in nature, and you will see multiple attempts claiming to ‘revolutionise’ analytics and insights, or ’rethink’ content management and automation.
But there are three broad areas of game changing technology which, in my experience, are worth pursuing, especially as they can all interlock to enhance digital marketing.
First coined in 1955, the term AI has featured in countless films and TV programmes, been the centre of heated Government debates around the world and is at the heart of most technical innovation.
Simply put, the machines have it better than humans. AI simply mirrors the best parts of our intelligence minus consciousness and emotion.
And, of course, it is only as effective as the algorithms behind the programming which is completed and maintained by – that’s right, you guessed it, human beings.
So you get complex task solving within an artificial environment, which won’t think too much about the meaning of life or sulk off.
I’ve personally worked alongside an AI “robo-writer” named Carmen, or to give her full name: Content Automated by Robots for the Monitor E-publishing Network. Carmen writes, on average, 50 articles a week for Investment Monitor spinning out guides to investing in Ecuador to Morocco, Jordan to France, replete with accurate financial and socioeconomic reporting.
Key takeaways for marketers:
→ Data is the most valuable asset when it comes to marketing. AI can collate data from multiple systems in seconds that would ordinarily take a human workforce days and weeks.
→ AI detects patterns in vast volumes of data and interprets their meaning for humans to act upon.
→ Time is freed up for the human workforce to focus on tasks that require more inquisitive and creative thinking (see: The robot journalist creating specialist content).
→ Consumers will benefit from improved website/portal experiences, as AI can help serve content and products based on accurate personalisation – this all comes from having the right data available.
→ AI is the technology behind chatbots; the industry is projected to grow from US$2.8bn in 2019 to $142bn by 2024 (see: Rise of the chatbots).
2/ Machine learning (ML)
Although strictly speaking part of the AI umbrella, it is worth spending a bit of time on the part of AI that makes its future truly mind-blowing.
Referring to the study of algorithms that improve through experience – and without explicitly being programmed to – it is perhaps the closest to a future where machines replace us and be relied upon to provide a semblance of ‘humanity’.
For now though, it is behind the advance implementation of AI within entertainment platforms such as Netflix and Spotify, search engines, social-media giants and voice assistants.
By finding patterns in numbers, words, images, clicks, ML can now make highly educated guesses about the user and what they might want to do next.
Black Swan Data used a machine learning algorithm to draw patterns from social media conversations in order to predict future tea drinking trends for Lipton Tea, with astonishing success.
Key takeaways for marketers:
→ ML will predominantly – at least short term – be used to predict a customer’s online journey, predict where and when to reach them with increasingly innovative personalisation.
→ By using systems designed to predict the intent of customers and consumers, this will enable new marketing workflows and allow marketers to focus on actually acting upon the data rather than researching it in the first place.
→ It is likely that an increased reliance and trust on this type of martech (ML with AI) will not only be cost-effective, but will also reduce the need for humans in certain departments, such as customer services and email marketing (think chatbots and automated nurture emails).
→ Most companies will already have roles responsible for interpreting data, but there will be more in the future, while others retrain (see: Why data journalism is vital to marketing).
3/ Propensity Modelling
Dating back to 1983, propensity modelling has always been the perfect fit for marketing and sales. Its modus operandi is simple: to mathematically predict someone’s most likely action.
Or for the purposes of marketing, the chances that visitors, leads and customers will buy, sign-up or accept an offer.
But it is only with the explosion of machine learning tech that propensity modelling has become a game changer.
Now this increasingly statistical approach to marketing is being combined with computer intelligence and learning, and it is not stopping for anybody (unless someone trips over the plug lead, naturally).
Consumer giants Procter and Gamble (P&G) credited their best quarter and fiscal-year sales growth back in 2019 to ‘propensity marketing’.
David Taylor, P&G Chairman of the Board, President and CEO, stated at the time:
“In the past, we’ve had broad demographic groups that we targeted.
“Once you have the smart audiences, you can do propensity marketing with people that have similar characteristics. [P&G is] reinventing brand building from wasteful mass marketing to mass one-to-one brand building fuelled by data and technology.”
Key takeaways for marketers:
→ As with most marketing campaigns, data is everything. By only using historical data, propensity modelling may not include current trends – although AI can help to scrape social media and online output to keep up-to-date.
→ Propensity modelling, ML and AI still (and probably always will) need the humans running the programmes, questioning and making the best use of data and improving the processes at every turn.
→ Hiring roles in this field will be difficult for smaller marketing departments and businesses as it is not seen as a priority – plus one pays for expertise.
→ Accurately predicting a potential customer’s behaviour and intent is only half the battle in marketing, albeit an important one to win. Those leads need to be converted from a marketing qualified lead (MQL – a hot lead but not ready for one-to-one attention from the sales team) to sales qualified lead (SQL – ready for one-to-one sales comms) and then… well then they need to spend money, use your services, partner up or take any other desired action relevant to your marketing objectives.
In a new era of tech spend…
Companies are already using intelligent and autonomous technologies to boost marketing performance. As digital marketing tech spend increases, it will be interesting to see how much is invested in these technologies. The capabilities are already there and will no doubt continue to improve.
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