This is the second installment of our three-part blog series in which we identify some of the biggest challenges for today’s online retailers and discuss how you can overcome them. If you haven’t already, read our first installment, Part One: Attaining Customer Loyalty in a Competitive Environment.
Part Two: Leveraging New Trends in Artificial Intelligence
“Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence.” - Ginni Rometty, CEO of IBM
Though science fiction writers may have expected us to be battling unruly robots in the streets by now, the world is far from the apocalyptic scenes of Terminator or the dark days of I, Robot. But much like Back to the Future wrongly predicted we’d all be commuting on hoverboards when in fact electric and driverless cars are the new heights of travel innovation, AI has come about in ways that writers and filmmakers didn’t quite expect. Yes, we have progressed, and we continue to progress in many aspects of life – but not in the way that means Will Smith’s robot Sonny has taken up the spare seat in our marketing department.
An Introduction to AI in Digital Marketing
From driverless cars, to suggested television viewing, to saving energy in your home, AI is very much present in our modern lives. But what exactly is AI, and where does it fit in for retail marketers?
What is artificial intelligence?
AI has been described as any task performed by a program or machine that would otherwise require human intelligence. In the examples above, AI is used to transport us on roads safely, to tell us what we should watch next based on our previous viewing history, and to analyse how we use power in our houses and where we could reduce our energy consumption. There are two types of AI – narrow AI and general AI. Narrow AI is programmed to carry out one specific task, such as spam filtering, facial recognition, or media recommendations. General AI is more sophisticated, and has the cognitive ability to cope with any task it’s asked to perform, much like a human – that’s what the sci-fi movies depict.
We’re a long way from general AI yet, so how does narrow AI appear in the digital marketing world? There are many areas in which AI can improve your customers’ experiences, provide you with meaningful data, and subsequently improve your ROI. Think chatbots, content creation, PPC automation, voice search and more. We’ll talk you through all of this so that you can get a picture of how you can use AI and machine learning to your competitive advantage.
The benefits of automation
Let’s start with PPC, where Google is making great strides in freeing up marketers’ time by eliminating the need to complete repetitive tasks. Automation is key for marketers these days and comes in a few different forms. You can now reap the benefits of machine learning to get the best possible return from your ads. Letting Google and Bing do some of the work for you will free you up to focus on more meaningful work. With these advancements, your PPC can deliver more clicks, conversions, or whatever your goal is – delivering a better ROI without requiring more time and resources.
What is machine learning?
Machine learning is just what it sounds like – a machine learning over time how best to complete a task, through observing and interacting with data. The more information and “experience” the system is given, the more accurate and useful its output should be. For example, if you’re watching Netflix, the shows it recommends you watch are more likely to be ones you like if you have watched fifty programmes on Netflix, than it would be if you had only given it five examples to work with. Similarly, for machine learning in terms of PPC, the more data such as clicks, impressions and conversions your account gets, the more likely it is to make good decisions and deliver better performance.
Why is AI a challenge for online retailers?
So, with automation and machine learning available to marketers, why does this pose a challenge for online retailers? Quite simply, if it’s available to you then it’s available for other retailers to use, so if you’re not taking advantage of it, someone else is and could be getting the conversions you would otherwise gain. Plus, if you’re not using a particular type of AI, such as a chatbot, your customers may feel that your competitors are more innovative than you are and that they provide features they really appreciate, whereas you don’t.
We’ve established that AI, machine learning and automation are all present in digital marketing. But how exactly can this help with your PPC? Here are a few features you can use in your Google Ads account, which can help you as a retailer to improve your marketing ROI.
Dynamic Search Ads
Unlike traditional PPC, dynamic search ads don’t target keywords but instead the content of the website forms the basis of campaign targeting. These ads are designed to enable you to target customers searching for exactly what you offer and can be used with all pages on your website, specific pages only, or a page feed. The ads then appear based on the search terms a customer uses, and they are taken to the most relevant page. These ads work best for websites with a big inventory, such as large retailers. Take a look at our blog post, “SilverDisc's Guide To Dynamic Search Ads” for more information.
Automated Bidding and Smart Bidding Strategies
Google’s automated bidding tool analyses the user’s Google profile, device, location, demographics and more to automatically modify your bids based on how likely the user is to click on the ad or convert. For example, you can use “maximise clicks” to get as many clicks as possible within your budget, “target search page location” to increase your ad’s visibility on the search results pages, or “target outranking share” to outrank competitors.
Smart bidding in Google Ads is a subset of automated bid strategies, including target CPA, target ROAS, maximise conversions, and enhanced CPC (ECPC). At Google Marketing Live 2019, the search engine also announced a new smart bidding strategy, “maximise conversion value”. With smart bidding, Google uses machine learning to predict which clicks are most likely to lead to conversions, based on previous data within your account – so the more data Google Ads has, the more accurate and effective these predictions are likely to be, and the more likely you are to reach your ROI goals.
Read our blog post ”Choosing the Right Automated Bidding Strategy for Your Business” for more information.
Google Ad Suggestions
Google Ad Suggestions suggest variants of existing ad copy to use in your ad groups, based on the content already in your ads, extensions, landing pages and keywords. A mixture of machine learning and human review helps to improve these suggestions. Find out more in our blog post ”An Insight To Google Ads Recent ‘Ad Suggestions’ Feature”.
Audiences in Google help you to target more potential customers than ever, using machine learning to build groups of people with similar interests or habits, people who have interacted with your business before, or who are researching something specific. Some examples of these tools are affinity audiences, in-market audiences, customer match, similar audiences, and remarketing audiences. Find out more about each one and which tools may help you to improve your ROI in our blog post “What is Audience Marketing – And Why is it Key to Your Digital Growth”.
Also announcing at Google Marketing Live, Bumper Machine is a new tool to help marketers create bumper ads. These six second video ads are ideal for mobile viewing, and they take content from existing videos you have already uploaded and use them to create three or four ads which you can then edit. They use AI to identify important parts of the video such as close-ups of people and text overlays, and put them together to create a cohesive message. This is AI at work creating new content for your ads.
Virtual Assistants and Voice Search
Another AI trend well worth keeping up with at the moment is the increased use of virtual assistants and voice search. For example, did you know that when you use voice search to ask your virtual assistant or smartphone a question, the information spoken back to you often comes from featured snippets? Featured snippets are those blocks of information that appear at the top of the search results pages, and they attempt to give the user an immediate answer to their query, along with a link to the website the information has come from. So, when a user asks Siri or Alexa a question about a product you happen to sell, the voice assistant may provide this featured snippet information and an opportunity to visit the website. You want that website to be yours rather than your competitor’s. Find out more about virtual assistants in our blog post “Could Google Introduce Paid Ads to Voice Assistant Search Results?” and read up on voice search in our post “Is Your Website Ready for the Voice Search Boom?”
Chat bots may not be able to help with very specific customer queries, but as a solution for answering basic questions about your products or business, especially out of normal operating hours, chat bots could be a useful tool. Especially if your competitors are using them, you don’t want to be lagging behind. Not only will customers go elsewhere – and be more likely to buy elsewhere if you can’t give them timely information when they need it – but your competitors will be seen as more technologically advanced. This may matter more if you’re an IT reseller compared to if you’re a fashion outlet, but as we know, your website says a lot about your company and if AI can benefit your customers, you should certainly consider how you can provide them with the technology they expect from you.
How Can AI Help You Increase and Enrich Your Data?
As you can see, there are so many ways in which AI can help you to gather more data about your customers, tap into new markets, and provide customers with the technology they crave. All of this is to say that the robots might not be taking over, but they can help you to overtake your competitors.
In terms of PPC, machine learning provides you with not only more data, but the automated tools for using this data in a more effective way and improving your ROI. When you have a large amount of data, that’s when automation and machine learning will really help, but you’ll also need to know how best to handle and analyse any data available to you, in order to make it as useful to you as possible. This leads us into our third and final installment in this series – “Handling and Analysing Big Data to Maximise Growth”.
Read the final part of this three-part blog series, in which we’ll take a look at the challenge of gathering, handling and analysing big data to give you a competitive advantage: Handling and Analysing Big Data to Maximise Growth.