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Artificial intelligence (AI) is coming for marketing. But don’t worry. Unlike some administrative posts and routine jobs like data entry, AI isn’t going to make marketing jobs obsolete. Instead, AI will make marketing teams much more efficient and productive.
AI for marketing analytics is a particularly fertile area. In this post, we’ll look at the benefits AI brings to marketing, assess some of the best AI tools out there for marketing analytics, and how to incorporate AI marketing analytics into your overall marketing program.
AI marketing analytics is the use of generative AI, automation, and other AI technologies to make rapid, data-driven decisions based on the analysis of data from online activity, such as clicks and form submissions, as well as offline interactions with customers, like phone calls.
AI’s ability to process and analyse very large datasets in real time and deliver analysis to inform marketing strategies, create content, and even predict future customer behavior makes AI marketing analytics an asset to the entire business.
Let’s dig a little deeper into some of the main ways AI helps take marketing analytics to new heights. Here are the most common use cases right now.
Sentiment analysis is a technique used to determine customer emotions and opinions expressed in customer communications. By analysing language and tone, businesses can gauge public sentiment — whether positive, neutral, or negative — toward their products, campaigns or brands so they can tailor their marketing messaging to help drive better results.
AI can be trained to recognise sentiment. It has the capacity to scan thousands of lines of digital text, such as social media posts, online reviews, and customer feedback forms to create a quick but accurate sentiment analysis of a business or brand.
AI can take sentiment analysis even further, though. With an AI-driven call tracking and analysis platform like Invoca, for example, you can gather sentiment from digitised phone conversations to hear the true voice of the customer. Using this conversation analytics technology can also help you gauge the sentiment of your customer service agents. So, if a conversation with a customer takes a negative turn because of something an agent says, you can pinpoint that moment and provide targeted coaching to the agent to help avoid similar situations in the future.
AI’s ability to collect, sort, and analyse very large datasets quickly and accurately means that marketing now has an incredibly valuable tool with which to identify trends in consumer behavior and develop insights that can be acted upon almost in real time.
Marketing data analysis is a highly labor-intensive, monotonous process for marketers relying primarily on human resources to get the job done. AI can make this analysis much more efficient and streamlined, helping marketers to be more productive and giving them more time to focus on executing and fine-tuning their marketing plans.
AI’s supercharged analysis can help marketing teams stay ahead of the customer but also quickly pivot when it’s clear a strategy isn’t working.
In fact, the ability to optimise marketing campaigns is greatly enhanced using AI. Marketers can improve campaign effectiveness and boost their marketing ROI based on the robust analysis of performance data provided by AI tools. For example, teams can quickly adjust ad spend to maximise ROAS using Google Ads’ AI-driven Smart Bidding tool.
You can supplement this bidding insight with data from offline conversions, too, if you have a tool like Invoca to help you pull data from phone conversations. Invoca’s Pay-Per-Click (PPC) optimisation tools can help marketing identify which campaigns are driving calls and surfacing the most qualified leads so bidding can be even more closely pinpointed to the best leads.
Online and offline data can also be analysed at scale by AI to help marketers efficiently segment customers into distinct groups based on behavior, demographics, and preferences. Customer segmentation allows marketing to target and personalise marketing and ad strategies.
For instance, say that the marketing team at your auto dealership uses Invoca’s AI tools to analyse data gathered from online activity and phone calls. They learn that most customers who call your dealership to inquire about SUVs are parents with young children. The team then develops a targeted ad campaign highlighting various features of the SUVs you sell that this customer segment would likely find appealing, such as safety features and cargo space.
Finally, AI’s ability to analyse data at scale makes forecasting future trends and customer behavior possible. That’s a tremendously powerful tool for marketers. Predictive analytics allows marketing teams to confidently anticipate customer needs rather than just reacting to them, providing a differentiator for brands over competitors who don’t use AI for marketing analysis.
Think of it this way: If you could know in advance which existing customers were likely to ditch your product or service, you’d be in a better position to win them over before they make the decision to cut ties. So, if your analysis of phone and other data shows that most customers leave after making three separate minor complaint calls to customer service, you could target customers after a second call with a preemptive discount offer or incentive to stay.
The array of tools that use AI to deliver in-depth marketing analytics to businesses is growing. Here are four examples of widely used solutions.
Yes, we’ll toot our own horn here! Invoca’s AI-powered conversation analytics is a valuable tool for developing marketing analytics because, even with transactions taking place online, many customers still prefer to transact over the phone. This is especially true for consumers considering high-value purchases such as taking out a life insurance policy, making a healthcare decision, or buying a car.
Invoca offers call tracking and analytics to create a more complete picture of customers and their needs and expectations by providing valuable insights into customer interactions that happen offline. This data analysis can inform marketing strategy and be combined with online data from PPC ad responses or web searches to help marketers better personalise customer outreach based on hyper-targeting and customer segmentation.
HubSpot is a cloud-based CRM platform with AI tools that businesses can use to manage marketing, sales, and customer relations. For marketing, HubSpot offers AI-powered content generators that automate the process of creating blog and social posts, marketing emails, and webpages. Marketers just type in commands and the AI creates text already optimised for SEO. Marketers can fine-tune the content through editing or use it as a starting point for content creation. The AI-driven platform helps personalise marketing efforts to improve lead generation and engagement.
Before ChatGPT, there was IBM Watson. IBM’s initial work with AI began in the 1950s with the exploration of foundational machine learning and natural language processing concepts. But it was the introduction of Watson in 2010 that showcased IBM’s AI capabilities in delivering predictive analytics and customer insights through machine learning.
In 2023, IBM introduced watsonx an AI and data platform that provides businesses with a suite of tools and infrastructure for building and managing their AI models. IBM watsonx can help marketers analyse large datasets to identify trends and optimise marketing strategies, deliver generative AI assistants to smooth the customer journey, generate content, and more.
Based on the premise that humans understand and retain more complex information in picture form, Tableau uses AI to create visualisations of complex marketing data — making it easier for marketers to analyse and understand customer trends. (Tableau’s own marketing states that its AI-driven visualisations for marketing analytics “speed time to insights by 29%.”)
Tableau’s interactive dashboards, campaign activity calendars, and analysis help marketers explore data and derive actionable insights for campaign optimisation and performance tracking.
There are many different AI marketing analytics tools to consider and compelling reasons to adopt one or more of them. So, what is the best way to implement AI into your marketing analysis and strategy? Here are four key steps we recommend marketers take.
Don’t bring AI into the equation until you’ve evaluated your existing data. Are you gathering data from a single source, such as online activity? If so, you are only getting part of the picture. While AI can do many things, it can’t be fully effective unless it uses large volumes of quality data.
Collect, clean, and scrub, and then consolidate data from multiple sources, such as your customer relationship management (CRM) system, social posts, website traffic and online data, and offline interactions like phone calls. This will provide your AI tools with a comprehensive dataset to analyse. Only then, can you be confident your results will be relevant.
To make the most of AI for marketing analytics, you need the right tool or set of tools. For example, if you are already awash in online data but aren’t capturing customer data from phone calls, you’ll want to consider employing Invoca’s AI tools to help you complete the picture.
It’s also important to choose solutions that will integrate well with your existing tech stack and CRM so you don’t create IT headaches and challenges for end users. Also, think about scalability. Your best course is to start small and expand. Go too big from the outset, and you may end up paying for features you don’t want or need.
Since you will be using AI to analyse customer data, you must also ensure the tools you select are secure and comply with all necessary privacy regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) or the General Data Protection Regulation (GDPR).
Never deploy new technology, especially AI tools, without also providing adequate user training. Train your marketing team to understand how to use these tools effectively, and make sure they can fully interpret AI-generated insights so they can apply them to strategy.
Hopefully, you are already fostering a data-driven culture in your marketing organisation. If you don’t, you’ll want to make it a high priority if you are serious about fully embracing data-driven marketing in the year ahead.
You’ll need a solid onboarding program to help your users ramp up with the technology. (Some AI vendors provide support for implementation.) You will also need to invest in ongoing education and resources. AI is rapidly advancing, so continuous learning is a must to keep your team up to date with emerging features and best practices.
Lastly, as with any technology, don’t just set it and forget it! Only by regularly monitoring AI-driven insights and marketing performance can you ensure the tools you are using are delivering value and meeting your business goals.
Remember that your customers’ preferences and behaviors are constantly changing. So, you must adjust your AI models to compensate for these changes, or your analysis will likely be skewed. Develop a regular review process and stick to it.
And, once your AI tools are ingrained in your marketing team’s workflow and delivering insights, don’t hesitate to make data-driven adjustments to your marketing strategies so you can continuously improve their effectiveness and ROI.
The more analytics you have at your fingertips, the smarter optimisations you can make to your marketing strategies. Invoca uses AI to capture insights from an often untapped source: the many phone conversations your contact centre agents have with customers and prospects every day. With Invoca in your AI toolset, you can more effectively analyse customer sentiment, retarget customers with relevant ads, and optimise your campaigns to drive more revenue.
If you are seeking more information on the benefits, use cases, and top tools for AI marketing analytics, see these additional resources from Invoca:
When you’re ready, you can set up a customised demo with Invoca to experience firsthand how our AI-driven tools can enhance your marketing strategy and boost performance and ROI.
