The road to AI in marketing

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Marketing departments in particular stand to gain vast benefit from using AI, most notably in their ability to deliver consistent experiences and exceed customer expectations. However many marketers are cautious in adopting new technologies, and as AI can be a massive task to implement, marketers stand to benefit from easing into the process of AI adoption by following the steps below.

Start with automation

Automation software enables marketers to automate repetitive tasks such as applying the correct branding to company documents. Whilst these are important tasks, they can impact on productivity and detract employees from focusing on more pressing matters within the business. This is supported by research conducted by McKinsey which found that 45% of work activities can be automated by implementing technology solutions. With automation, companies will benefit from cost savings, improved productivity and improved reliability.

Before implementing brand automation, marketers need to conduct a brand audit to determine how the brand compares to its competition, what the brand strengths are, how customers interact with the brand and where the key customer touchpoints are. It is important to look broadly beyond a specific department and include the “messy and complex” things too as this is often the stuff that no-one wants to do but that will provide the most valuable insights.

For example, marketers may suggest that email signatures are the responsibility of the IT department, however, customers don’t discriminate between the internal departments within a company, they expect their needs to be met and view the organisation as a whole regardless of who they engage with. As such every element of the brand should be audited.

Once you have conducted a brand audit, the next step is to determine which functions can be automated. These are the functions that require a time investment from staff but deliver minimal return on the investment.

For example, complex customer requests should be handled by employees but if a customer is calling for a statement, this process could be automated to free up employees to handle the more challenging customer issues. The most important thing to remember when automating tasks is that customers are often looking for human interaction, particularly when dealing with sensitive or complex issues.

In the case of the customer experience, companies need to get the balance right between what can be automated and what should be handled by employees. Ultimately the best approach is to remove human intervention from the repetitive and menial tasks in order to free them up to handle the more important and complex functions that make the real difference to customers and ultimately build the brand. Once these functions have been identified the next step is to identify patterns within customer engagement by analysing the data.

Moving beyond automation

For many years marketers have been collecting customer data but haven’t been able to use it effectively until now. With a mountain of data, combined with established parameters, technology is able to move beyond mere automation to bring marketers intelligent and intuitive offerings. For example, in the case of email, employees could select predeveloped content to drop into emails they send to customers.

Initially, this would require these employees to make decisions in terms of which content to select, however, over time the technology would become intelligent and intuitive and combining the data with usage patterns, it would simplify the process even further for users by automatically inserting the correct content for the recipient.

However, marketers should also pay attention to unstructured data as this is where the real magic lies. By identifying patterns in unstructured data, you’ll be able to find opportunities to innovate and identify real behaviours rather than rely on what people say they are doing. With greater insight into who your customers are and a clearer understanding of their needs, it is easier for employees to engage with them using relevant, personalised information, sent at the right time and improving the overall customer experience.

Introducing AI tools

Once marketers have become comfortable using these technologies, the next step would be to assess their business needs to determine which AI applications are the best suited to meet their specific needs. There are several AI solutions available and marketers should be cautious not to implement AI for AI’s sake but rather determine which solutions are best suited to help them achieve their business objectives.

It is also important that you consider the legacy systems within the organisation as this can often be a stumbling block to implementing new technologies. Marketers need to clearly articulate their requirements and collaborate with the IT department to implement solutions that meet the business needs.

The most imminent AI solutions available for marketers include anticipating future customer purchases and presenting offers accordingly, improving media buying, monitoring social media comments to determine brand affinity and tailoring promotions. However, this is only the tip of the iceberg in terms of what AI can bring to the marketing table.

With the correct data combined with the right AI solutions, marketers are able to gain greater insight into customer sentiment and behaviour to more proactively plan and target campaigns that deliver the best results and enhance the customer experience across every customer touchpoint.

Get started now

There is no doubt that AI brings about some uncertainty with the promise of great things for marketers and business. While still in its infancy, this is the time for marketers to slowly start implementing technologies that lay the foundation for AI at a later stage. Marketers should start getting familiar with automation technology and determine exactly what they expect from AI technology before making the leap and introducing AI solutions into the organisation.

While it can be tempting to jump in head first, by adopting a slow and steady approach to AI implementation, they will be setting themselves up for success in the long-term. But the time to start is now.