How AI is impacting the digital marketing industry
Artificial intelligence (AI) is becoming an integral part of our day to day lives – even if we don’t always know it. From the adverts we see on our social media feeds or Google searches to the cybersecurity protection we get on our phones, computers, and networks – AI is having an impact on many industries around the world, and digital marketing is no exception.
AI is now helping to shape a new digital era and its impact is already significant and continuing to grow. AI, along with machine learning (ML) is helping companies to develop more robust and data-driven digital strategies, optimise campaigns and improve ROI.
AI and ML are revolutionising the way businesses attract, retain and service their customers. Using data insights, businesses are using AI as a way to create business advantage, however, it is only a matter of time before more businesses jump on board and start to maximise the benefits of using AI in digital marketing.
Whilst it’s easy to talk about the impact of AI on digital marketing, what does it actually look like in real life?
Here are seven real-world applications of AI in digital marketing, many of which will already be impacting you whether you work in digital marketing or as a consumer.
1. Search Engines
As you might expect, search engines were one of the earliest adopters of AI and Google officially confirmed the rollout of a machine learning AI called RankBrain in 2015.
RankBrain is a query-filtering process that learns from each user query and applies those learnings to each successive query.
Machine learning AI in search helps Google to recognise the natural language that people use when they search online and use this information to provide more relevant search results.
This is perhaps the biggest example of how AI is impacting all our lives, whether we know it or not. Google is utilising the immense power of AI and ML to analyse billions of data queries and learn from each and everyone, helping to deliver a better customer experience by providing the most relevant results to search queries.
RankBrain will continue to develop and change, especially as more and more people make the move to voice search where it will learn and adapt to the natural language people use when searching using voice commands rather than typing.
2. Customer profiling
Big brands are already utilising AI and ML to reveal deep insights about customers’ shopping habits, motivations and needs. Consumers have been a relatively untapped source of information for years, due to the amount of data they produce and the difficulty in pulling all that data together and producing valuable analysis and insights.
Now, AI is helping to utilise that data and identify patterns and trends that are helping brands to make more informed decisions.
Many businesses still rely on fictional personas and whilst these are typically data-driven, they are not real-time. They are typically based on information gathered through surveys with existing and potential customers to help form a realistic profile of what an ideal customer would look like.
AI and ML are helping to process data in real-time and provide customer profiles that are not only based on real-time data, but that also tackle every single customer, helping you to uncover audience segments you never knew existed, allowing you to target these new prospects with marketing activity.
3. Content curation and recommendations
Most of us are familiar with the “you might also like” recommendations that we see not only on e-commerce websites but also on the blogs and articles we read.
Traditionally, these have been generated manually, or through category association – if you are interested in a pair of men’s jeans, then there is a good chance you will be interested in a men’s shirt or men’s underwear for example.
Whilst this is a crude way of getting customers to add more items to their cart or read more articles on your site, like customer profiling, it is not real-time.
With AI and ML, your behaviour on a website can be tracked and more personalised recommendations provided, based on your interactions on the site. AI and ML analyse huge chunks of data about people’s behaviour online to determine what they are most likely to want to do next.
4. Customer support services
Another AI-driven tool we will all be fairly familiar with is customer support. AI is allowing businesses to provide 24/7 customer service for customers, with instant responses to customers queries and faster resolutions to enquiries and queries.
This is especially true for global brands, where customers expect to be able to access customer support, no matter the time of day in their country. According to research carried out by social media giant, Sprout Social, they found that 40% of consumers expect a response within an hour of reaching out on social media. That is virtually impossible without the use of AI.
AI-powered chatbots have been around for a number of years now, and they are becoming more accessible to businesses large and small. AI-chatbots actually put the emphasis back on the consumer to find the answers to the questions they have. Early AI-powered chatbots would simply provide a stock-standard response to customers, however, things have come a long way and now AI-chatbots are capable of generating original responses to customer queries.
Expect to see the use of AI-powered chatbots for more than just customer service in the future. Brands like Sephora are already using AI chatbots as a new way for consumers to engage with their brand.
Sephora’s chatbots already handle customer queries, store reservations and provide make-up tips, video tutorials and product reviews.
5. Ad targeting
This is another AI-powered tool that most of us will encounter, even if we don’t know it. AI is quickly becoming an essential tool for advertising campaigns. Long gone are the days of manually analysing Ad performance and optimising your campaigns based on your understanding of those results.
AI and ML can process huge amounts of data to provide you with the insights you need to optimise your campaigns and drive more clicks, sales and revenue.
Programmatic advertising is becoming more commonplace and using predictive analytics, businesses are able to automatically purchase advertising space, with AI deciding which ads to buy and how much budget should be allocated. Whilst there is a learning curve, the more data your AI-powered platform has to work with, the better the understanding and the better the results.
Starbucks has been using AI to pull data from customer loyalty cards and their app to deliver personalised advertising based on user behaviour since 2016.
Since then, they’ve built quite the app experience. It records the details of purchases, including where they are made and at what time of day. Starbucks uses predictive analytics to process this data and serve customers with personalized marketing messages. These messages include recommendations when a user approaches a local store and special offers to increase the customer’s average order value.
6. Social listening
Brands have been monitoring social media platforms for a number of years now, however, this has typically meant setting up active “listening” tools to monitor brand mentions and topics relating to the business.
As social media platforms continue to grow and evolve, manual monitoring has become more difficult. AI is helping brands to analyse social media posts and comments at scale, enabling brands not only to track mentions but also to highlight trends and patterns.
Using AI-powered technology, brands can now identify when a brand is mentioned in comments. Enabling them to jump into conversations where relevant.
The amount of data that can be collated and analysed using AI is much greater than manual monitoring tools, providing invaluable insights that allow companies to conduct extensive market research.
CampaignLive reported how Consumer goods company Unilever uses AI data centres across the globe to synthesize insights from a range of sources, including social listening, CRM, and traditional marketing research. Using this technology, Unilever discovered a link between ice cream and breakfast: at least 50 songs in the public domain include lyrics that talk about “ice cream for breakfast”.
“The machine-learning algorithm crunches all this data and we’ve now learned there’s an opportunity for going after sweet breakfast items. Two years down the road and our competitors are now doing the same,” said Stan Sthanunathan, Unilever Head of Insights.
7. Content recommendations and creation
Copywriting is hard. It is time-consuming, and it requires a lot of skill and understanding. Whether you are writing product descriptions or PPC ads, meta descriptions of how-to guide posts, there is a huge volume of work required and sometimes the repetitive nature of the work can take its toll on your creativity.
AI is now helping businesses to write copy, using natural language processing tools. Based on some basic parameters (entered by you), AI-powered copywriting tools will analyse millions of examples of pre-existing content on the same topic from around the web and process that information into something unique and plagiarism-free.
AdAge reported in July 2019 that Chase Bank in the US had committed to AI after machines had outperformed humans in a copywriting trial. The bank announced a five-year deal with New York-based Persado – a company that specialises in AI for marketing creative. Remarkably, Chase found that using machine learning in their copywriting helped them to achieve more humanity in their marketing.
“They made a couple of changes that made sense and I was like, ‘Why were we so dumb that we didn’t figure that out?’” said Kristin Lemkau, chief marketing officer at JPMorgan Chase. “And some of them weren’t intuitive—like they added words to one of the headlines, where a marketer would have thought you should take it out and add more white space.”
For example, one digital ad written by humans read: “Access cash from the equity in your home.” Persado’s version, on the other hand, read: “It’s true—You can unlock cash from the equity in your home.”
The Persado version generated 47 weekly applications for home equity lines of credit, compared with 25 for the original version, JPMorgan Chase said.
Artificial intelligence is playing a part in many aspects of our lives today, whether we know it or not and digital marketers are really embracing the opportunities that AI is providing in the digital space.
The next time you get annoyed by an ad, or a search result that doesn’t quite meet your needs, remember, it was probably generated by AI.