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Using Artificial Intelligence In Your Marketing

Artificial intelligence and machine learning are still the buzz words for 2019 and are becoming increasingly important in the marketing industry. But what does it actually mean to put AI into practice in your marketing campaigns?

Here are some great examples of AI put in action in the marketing industry.

  1. Data analysis

Collecting great data is key to driving improvements in the customer experience and personalisation, however, consolidating these large amounts of data once it has been collected, and analysing it to determine patterns, is can be difficult. One of the great strengths of AI in the workplace is its ability to take on complex analysis tasks that would be difficult for humans to carry out – thus freeing up time for marketers to do more intuitive, creative work.

  • Segmentation

The extent to which marketers can segment their consumers comes down to the data that they have – segments can be as simple as gender and age, or as complex as past behaviours and buying personas. AI-based Dynamic segmentation takes into account the fact that customers’ behaviours are rarely fixed and that people can take on different personas at different times for different reasons.

  • Product recommendations

The most successful giants in digital – Amazon, Netflix and Sky – have already built their product offerings around the ability to provide highly relevant and personalised product or content recommendations. This is done through AI-powered recommendations – collating and interpreting consumer data paired with profile information and demographics. The AI-based systems continually adapt to your likes and dislikes and react with new recommendations.

As we become used to the level of personalised recommendations provided by these services, we then expect other brands to follow suit.

  • Social listening

For marketers wanting to analyse their brand presence and conversations around their brand on social media AI is a great tool. It allows brands to perform sentiment analysis on social conversations and understand the prevailing attitude towards their brand and products. This can allow them to spot potential issues and counteract them before they become too widespread. It can also be used to spot purchase intent by analysing the ways that consumers are talking about a product – for instance, “Shall I upgrade my iphone?” which can enable marketers to target them with advertising or a strategically-placed discount. Remember to be careful with the targeting, too much and you can risk appearing to stalk a consumer.

  • Product pricing

The travel industry has long use the demand-based price model – think hotel room rates and flight prices changing with availability and seasons – but by using AI prices can be optimised using a wide variety of data into account. Dynamic pricing analyses a customer’s data patterns and predicts what they are likely to be willing to pay, and also their receptiveness to special offers.  It can also be used to compare your product pricing with that of your competitors, to determine if their pricing is too high, about the same, or too low.

AirBnB is a classic example of a brand that uses an extremely sophisticated dynamic pricing system. This helps property owners determine the price that they should list their property taking into account factors including geographic location, listing features, photographs and reviews, as well as market demand and time to booking date.

  • Speech recognition

Speech recognition technology and natural language processing has advanced massively in recent years – in 2017 Google’s level of speech recognition accuracy reaching the 95% threshold. This has meant the use of voice-activated devices has grown in the marketing industry. Speech recognition plays an important role in making sure that voice interactions function smoothly, and that a users requests, be in on a phone or via a laptop, are interpreted correctly.

Here we have looked a few ways that AI can be used in marketing to change the way that we work, shop, and sell, However, it is is by no means all-powerful – remember that AI and machine learning still need people.

Brian Bergstein, writing for the MIT Technology Review summed it up perfectly:

“AI might eventually transform the economy—by making new products and new business models possible, by predicting things humans couldn’t have foreseen, and by relieving employees of drudgery. But that could take longer than hoped or feared, depending on where you sit”.