4 practical uses of artificial intelligence in marketing

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Artificial intelligence (AI) has come a long way since its inception – with major breakthroughs taking place as we speak. It has often been brushed off as unrealistic, too futuristic or too expensive for someone other than the likes of Amazon or Netflix to implement, but this is no longer the case. In this article, we take a look at four examples of the kind of artificial intelligence for marketing that companies like yours are using to get ahead of the game.

1. Personalised content/product recommendations

Be relevant, be timely and don’t pester me with irrelevant deals – that’s what your typical customer now demands. According to the latest Salesforce report, 62% of B2B buyers expect to receive personalised recommendations at different stages of their journey. In the B2C segment, shoppers are even more spoiled and expect an Amazon-ish kind of experience from every brand. Segment’s 2017 study noted that only 22% of customers were fully satisfied with the level of personalisation they received.

Machine learning – the power behind most content recommendation systems, including those of Spotify, Netflix and Amazon – can appear out of reach for marketers due to price and technology constraints. However, developing custom algorithms isn’t the only way to go. Plug and play solutions are now plentiful on the market and are a quick and efficient way to use artificial intelligence in marketing. Some examples are:

  • Content AI by Marketo – which uses predictive analytics and machine learning to display the most relevant content on your website as “recommended” for users.
  • CaliberMind – analyses all your customer data, creates ideal buyer personas, and suggests how to communicate with your audiences in a profitable way.
  • Visely – an AI-powered product recommendation engine for Shopify stores.

Wondering how quantifiable the impact of AI on personalisation is? After analysing 3.5 billion marketing interactions, Blueshift concluded that AI-powered personalisation:

  • Creates a 3.1X-7.2X lift in customer engagement.
  • Has 2X higher impact on engagement for mobile pics compared to email.
  • Over time, AI engines can deliver an additional 50% lift over the initial results.

2. Conversational AI – chatbots

Chatbots are the driving force of automation in customer support, but sadly they are underemployed in the marketing space. After all, marketing is all about cultivating great relationships and leading meaningful conversations. Chatbots can now cope perfectly with that task, helping you engage with prospects through multiple channels at different stages of their journey.

For instance, Nordstrom allows shoppers to engage with a bot whenever they are looking for a gift. After asking a series of leading questions, the on-site assistant suggests the most appropriate goods to buy.

Nordstrom chatbot showing a conversation
Nordstrom chatbot

The Hipmunk Messenger chatbot takes the user’s location to determine where they are travelling from and then pitches appropriate deals. Their clever assistant can also curate travel advice and manage hotel bookings for the upcoming trip. The travel industry in general already leads the way when it comes to chatbots.

Hipmunk chatbot
Hipmunk chatbot

Other industries are catching up as well. In fact, between 2018 and 2024 the global chatbot market is expected to witness a 31% growth and reach $1.34 billion. This should come as no surprise, considering the shrinking costs of developing a chatbot. According to CMS Wire, the average cost of an SME Messenger chatbot developed for marketing purposes is $3,000-$5,000. But, remember, beyond giving your bot the AI wits, you should also account for the content development costs.

3. Predictive analytics and insights

Better use of data for audience segmentation and targeting is a top priority for 55% of marketers in 2019. If you want to follow suit, you need to move away from just using descriptive analytics (Google Analytics) and embrace predictive tools.

Predictive and lately prescriptive analytics can help you beat the data chaos and pinpoint the most profitable marketing channels and actions. Machine learning algorithms are already at your service to help you:

  • Anticipate and react to changing consumer behaviours.
  • Score leads in your CRM and suggest the best move to meet your sales numbers.
  • Optimise your PPC budgets to increase sales without spiking your ad spending.
  • Identify and acquire “lookalike” prospects, closely matching your ideal buyer personas.
  • Discover and pursue missed keyword and content marketing opportunities.

The best part? Predictive analytics is now a commodity technology, within reach for both SMEs and larger enterprises. In fact, smaller companies often have a competitive advantage when it comes to predictive analytics adoption – they need less time and technological effort to prepare their data for analysis.

[Read how Apollo Insights can help you obtain at least 4X more insights than your competitors]

4. Social listening and sentiment analysis

Knowing what people say about your company (or your competitors) online is essential for creating an effective social media marketing strategy. But detangling insights from that hot mess of conversations happening simultaneously is a better job for AI than a human agent.

Data science is already being actively applied to social media marketing for micro-segmentation and targeting, social media listening and influencer marketing campaign management. AI-powered social listening stretches marketers’ abilities even further, allowing them to:

  • Identify and quantify consumer purchase intent on social media.
  • Understand how shoppers feel about your product vs your competitor’s product.
  • Learn what’s driving the conversations in your industry and how the content of those conversations changes over time.
  • Notice and respond to questions about your products/services in real-time.
  • Identify and engage with buyers seeking product recommendations/advice on social media.

What’s even better  – AI tools can help you avoid the faux pas of including an avid surfer raving about a “great tide the other day” as opposed to a fan of “Tide, the detergent”.

To wrap up – Yes, you should definitely start to use more artificial intelligence in marketing as it can majorly increase the accuracy and effectiveness of your efforts. No, ‘smart’ tools are no longer exorbitantly pricey or useful only for selected industries. Jumping on the AI innovation train has become easier than ever, so if you’ve not done so already then it’s time to hop aboard.

Want to start using artificial intelligence in your marketing?

Then get in touch with our team today. We can give you a demo of our AI software, Apollo Insights, which is saving our customers hundreds of man hours and providing them with insights they might never have discovered manually. Call us today on 02392 830281 or submit your details here and we’ll call you.

George Karapalidis profile picture
George Karapalidis

George is an SEO Specialist and Data Scientist in the Portsmouth office. He has worked in E-Commerce and Digital Marketing across many industries, for and with companies all over Europe. Before joining Vertical Leap, George worked as Marketing Director for his own company, for which he managed to expand the company’s activities to 5 European countries. George has been creating websites for more than 10 years and he has in depth experience in designing and bringing optimised E-Commerce websites to market.

More articles by George
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