Artificial Intelligence (AI) is making inroads into many aspects of both industry and everyday life and marketing is no exception. As a powerful analytics and decision-making tool, AI can take much of the drudgery away from optimizing campaigns, as well as providing better insights about potential customers and how to serve them better.

Analysing Pay per Click

One of the major uses for AI in marketing is in PPC advertising. AI PPC tools take your data and combine it with their own, analyze it and make recommendations. It works by finding phrases your competitors are using and flags up opportunities you may have missed. It will point out search terms you could be using in your own campaigns.

The tool can then take these phrases and run them against Google’s own algorithm, making further suggestions. This can be done in real-time, allowing you to optimize your PPC strategy hour-by-hour and day-by-day, without the need to make manual adjustments.

Another related challenge is knowing where to place adverts and messaging. Programmatic advertising platforms use machine learning to bid on the most relevant ad space. Using data on interests, locations and purchase history, the platforms allow marketing teams to target the right channels for their campaign at the correct time.

Social media

Social media has taken the word by storm and has become one of the major tools in the marketer’s toolbox. In fact, it is probably today’s biggest and most dynamic form of marketing.

AI can do a great deal to make it even more useful, with tools to autogenerate social media content as well as automatically including hashtags and short links to other content. AI also offers tools to automatically schedule social media shares and for some types of social media, it can help create ads and manage them in minutes.

Tools exist to optimize social media campaigns and discover which posts work best using advanced analytics. AI can also be used to measure trends across each social media channel and find the target audience you are looking for.

It can also analyse what is being said on social media, making use of techniques such as Natural language Processing, or NLP, to analyse what is being said about your product and help determine the level of customer satisfaction you are achieving. Using this data, AI can track mentions of your brand, find emerging trends, new audiences and keep track of your reputation.

Predictive analysis

Understanding what someone is likely to want next is a major goal of marketers, who can then respond with timely content or offers to suit a potential customer’s needs.

AI can help marketers assess how likely it is that a user would use a service or buy a product. It can also predict which products are more likely to generate interest as well as finding the most brand loyal customers and those who might possibly turn to other vendors or providers.

Understanding the types of products, a customer will be looking for and when allows marketers to position campaigns more accurately.

AI can also help marketing teams track ROI, allowing them to see which campaigns contributed most.

Lead scoring

AI is great at uncovering things that affect whether or not someone is likely to become a customer. For example, machine learning models can score marketing leads using a wide variety of factors. This can help the model learn about the leads that became opportunities and those that went further to actually create revenue.

Each lead can be evaluated and scored by looking at customer behaviour, company size, industry and other factors, resulting in a ranked list of leads that sales representatives can follow up. AI can also provide reason codes for each lead, allowing sales to see the key factors that make the lead valuable. This ensures that sales get the highest quality leads, helping them achieve quotas more quickly and giving lower sales costs.

Language processing

The ability of AI systems to process and analyse human language allows the input from the customer to be converted into something that can produce the correct response or content.

NLP allows chatbots to augment customer service agents, allowing customers with more basic queries to be answered cost-effectively with immediate, accurate answers. The scans use historical data and previous answers to give personalized results for each customer. Customer service agents can then use their time to deal with complicated enquiries that require the human touch.

Advances in speech recognition and NLP have allowed Google to achieve a speech recognition accuracy rate of 95 per cent, leading to searches becoming better and improving consumer experience.

AI is opening up a whole new world of opportunities for marketers, bringing powerful tools and techniques that ensure campaigns are more targeted, cost-effective and above all, successful.