Understanding AI will help your agency, advertiser pitches

By Mark Challinor

INMA

London, United Kingdom

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In this newsletter, I will examine how we can use AI to create a better customer experience (UX) and an understanding of our advertisers’ needs in the modern age. Better UX can lead to more meaningful customer engagement for our advertisers’ use and ultimately more revenue for our companies in the process.  

I will also talk about a specific example, which, in my opinion, reinforces my points below about using AI well. The desire to give a better UX has recently reached new highs here in London, UK. The bar is being continually raised in the area, and we would be foolish to ignore what’s happening around us when dealing with our advertisers. We must understand why we need to offer creative excellence in our advertising endeavours. 

AI was a main focus in our recent Advertising Initiative Master Class where media houses across the world — from the South China Morning Post to NYC’S Bloomberg Media to the UK’s Daily Mirror — showed how they now segment their audiences using first-party data and are able to apply the equation I have talked about for years now, that is, the future of media centres around:

Data + Technology + Creativity = Better UX 

The first item (data) in this equation requires us to use AI, which normally starts with mounds of unorganised data. Yet, the benefits our advertisers (and our own media houses alike) have seen in their advertising and marketing strategies are immense with regards to the resulting creative executions and sales/engagement results.

The benefits of AI are incredible for media advertising strategies.
The benefits of AI are incredible for media advertising strategies.

So, let’s examine what those benefits actually are when you want to (and who doesn’t?) improve the client customer experience in their journey with your advertisers’ brands. 

In the words of Mike Beckerman from Torstar, Canada, in a recent INMA Webinar: “How do we understand and get on the radar of media planners and buyers? By helping the buyer buy.” In other words, by understanding the issues and hurdles that may be on their minds and demonstrating that we can — having understood the marketplace — offer impactful, creative solutions accordingly. 

I think there are six things we can highlight: 

1. Advertising clients should feel they are working with world-class media. 

As we learned in the Master Class, machine learning (ML) and AI aid natural language processing (NLP), which in turn, allows for the ordered arrangement, best optimised, and simple generation of content … rapidly.                                              

From an advertiser’s point of view, this saves resource (i.e. time/money) by processing huge amounts of data/content that can be easily searched for and tagged.                              

At the consumer end, this helps guide him/her through the customer journey with relative ease. Otherwise, people will feel discouraged from continuing to engage with the advertiser’s brand.

And that’s where AI joins the party. It allows advertisers to make decisions on what a customer’s next reaction might be, continually building on previous interactions/engagements to educate and inform what will come next.

Can we show we understand this with our advertisers? Do we have the right technology in place to offer this? 

2. Your advertisers’ customers need to feel they are understood, too!

Computers and platforms can process lots of data and take the strain away from the sales team and the consequent drain on resource. In turn, this then enables sales people to spend more time analysing client customers’ behavioural traits re purchases, desires and engagement.

We need to use ML to build profiles/personas and then create models that can predict what customers might do next, what they might buy, and perhaps what kind of messages they are going to respond to most.

Again, getting closer to our advertisers — by extracting, manipulating, then exploiting previous campaign data for them — allows us insights they may not have considered and values us more to them as we help them target what should then be happy customers, who feel valued, too.

3. Personalised content to get closer still. 

Targeting audiences via detailed database segmentation (via AI), allows each persona’s profile to becomes highly personalised over time. It means you can treat customers more like a true individual.

Creativity plays a big role in this process, too. You should maybe think about which colours, which headline, the message timing, etc. These all create an environment for customers to engage with the advertiser’s brand. They can massively strengthen the affinity and bond towards the advertised brand.

Deploying ML can unlock a big, potential opportunity to personalise across all your channels. And with the machines doing all the “heavy,” laborious work, you and your advertisers then have more time to scrutinise any insights gained. And you, the media brand, will be seen as the hero who helped them achieve that

4. Customers need to get appropriate messaging and recommendations.                  

When we see an irrelevant ad, especially in a place where we feel “at home” (a page where perhaps, we think the advertiser should know us well — eg for me, my local football team’s site or a commerce site I have bought regularly from in the past), it can be quite annoying. You feel that the advertiser either doesn’t really know you or doesn’t care.

Readers generally welcome recommendations that accurately reflect their preferences.
Readers generally welcome recommendations that accurately reflect their preferences.

I once got a message from an e-commerce site where I received a recommendation saying, “You recently bought a green jumper. Here are six more things that are green.”

You get the picture?

ML algorithms can forecast consumer behaviour to deliver to them highly personalised goods, offers, messages, appropriate content, and loyalty rewards. Do you consider all these factors? And the impact on the customer is fantastic. When customers receive for example, intelligent recommendations, it’s something they appreciate, and will give a halo effect to the advertising brand.

5. Customer service 2.0 (virtually)                  

We can see from the above how AI allows advertisers to provide better customer experience. Virtual assistants and bots in a brand’s Web site, newsletters, apps, and e-mails also enhances this further, with a one-on-one communication that, again, can be highly relevant and personalised to the individual customer.

This “conversational AI” as it is known, ultimately sits at the crossroads of customer engagement and customer needs. It can maybe, welcome a customer (by his/her first name), ask them if they need a problem solved, recommend relevant (key word, relevant) products and services based on the conversation you’re having now or on the last visit or even a past purchase.                     

Advertisers can also use the insights later on. When a customer returns to your site, the knowledge garnered from any past engagement will help brands instantly entwine themselves with those customers with more, highly relevant content

6. Make them look like experts to reap the rewards                                         

Advertisers and agencies are realising more and more the need for AI in their advertising campaigns, But, in my experience working with agencies particularly, don’t be surprised if you encounter many (but not all, obviously) inexperienced planners and buyers who will be really grateful for your expertise, insights, and direction.

Understand the environment in which they are working. Show them you have the expertise to help them. It makes them look great and will bond them to you when planning their next consumers after being more clever these days.

They expect more from brands now. They question brands more on what their rationales are for, say, asking for data or opinions.    

Understand this and, as the amount of data increases, the ability for us to make sense of it and applying it will become much more important. Advertisers are under increasing pressure to give bespoke, personalised experiences … understanding how AI can help is half the battle to securing more ad revenue for ourselves. Education is king. AI is the king’s beverage of choice.                      

Maybe that’s more than just waking up and smelling the coffee but something far stronger and more powerful? 

Further reading

Customer experience reaches new highs with smarter advertising data and technology

In embracing the equation of Data + Technology + Creativity = Better UX,  a new, intelligent, and very smart way (in all senses of the word, smart) to target audiences has emerged in the form a new digital billboard in the heart of London. 

The several-story digital billboard in London's Piccadilly Circus uses image recognition to personalise ads for passers-by.
The several-story digital billboard in London's Piccadilly Circus uses image recognition to personalise ads for passers-by.

At London’s Piccadilly Circus, the giant electric poster uses image recognition technology to display targeted advertisements based on factors such as the specific make of cars driving past or the gender/age of people walking by. 

It sounds like scene from the futuristic movie Minority Report, where a voice asks Tom Cruise, by name, if he would like a Guinness when he walks past a poster for the famous, black, alcoholic beverage. Or when in a Gap Store, a hologram recommends a type of clothing to suit his appearance? But no, this is real.

Smart, interactive advertisements are here to stay.
Smart, interactive advertisements are here to stay.

These large ad screens wrap themselves around the surrounding buildings, which overlook one of the capital’s most popular tourist destinations. Built-in cameras hidden inside the screens can track the make, model, and even colour of the cars driving past to deliver targeted adverts to the specific audience. 

Advertisers can pre-programme specific video ads to play when particular cars drive by … and adapt to the age or gender of a pedestrian. The cameras and a machine learning based algorithm, registers visual cues, for example, hair length and height and makes assumptions on the demographics of the area. So, if the algorithm detects a higher proportion of women in the area at any one time, it could display promotions for say, women’s clothing.

The technology can also be used to react to changes in the news, weather, sports, and social media updates. People can engage with the brands shown on the screen using social media platforms, too. This can then be used by the advertisers to project ads that best represent the interests of people in the area.

Impressive stuff. But you may be asking: Why am I’m telling you all this? 

It’s because it demonstrates why we need to be on top of our game.

When we deal with our advertising clients, we need to be ahead of the curve in terms of understanding their environment, their media choices, what else they are being bombarded with (be it, new tech as above or existing channels), what are the advantages and disadvantages of their choices, what budgetary constraints may apply etc?

And all the above, when stacked up against our own media offerings, shows us that our sales teams need to be highly educated to be able to compete. 

Once again, education is king. 

Further reading

About this newsletter 

Today’s newsletter is written by Mark Challinor, based in London and lead for the INMA Advertising Initiative. Mark will share research, case studies, and thought leadership on the topic of global news media advertising. Sign up for the newsletter here.

This newsletter is a public face of the Advertising Initiative by INMA, outlined here.

E-mail Mark at mark.challinor@inma.org with thoughts, suggestions, and questions or follow him on Twitter (@challinor).

About Mark Challinor

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