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.
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.
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?
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