Enhancing and personalizing your customer experience with artificial intelligence technologies isn’t a distant pipedream, as interviews for my recent report on AI-Powered Marketing for Asset Managers reveal. At one asset management firm, the business intelligence team is clustering advisor cohorts using machine learning models that mine transactional, demographic and behavioral data. At another firm, attribution analysis is being produced much more efficiently for each client using natural language generation technology, and yet another firm is using content intelligence technology that identifies thought leadership gaps the editorial team should address.
Why you need AI-powered marketing
Being relevant and personal, with the help of artificial intelligence, delivers returns on your marketing investment. Industry research finds that personalization can reduce acquisition costs by as much as 50 percent, lift revenues by 5–15 percent, and increase the efficiency of marketing spend by 10–30 percent.
In fact, our annual survey of financial advisors found that, when choosing among fund managers with similar products and comparable performance, a personalized and relevant digital experience tips the balance for 3 of 4 advisors.
You can’t implement sophisticated personalization across your entire audience with traditional marketing. Being relevant at scale requires creating and delivering hundreds of thousands of highly relevant interactions to existing and potential clients. What firms typically create — one-size-fits-all content — is at odds with the personalized answers and solutions each advisor needs. Closing that gap requires AI technologies like machine learning, natural language generation and digital assistants. That’s why there’s an emerging consensus that AI will become a de facto organizational competency for marketers by the end of 2018.
What you need to get started
There’s no time like the present to explore what you can do with AI. Here are three simple ways to get started:
- Review the capabilities you already have. If you are unfamiliar with the full range of capabilities your systems have for marketing automation, content management or content syndication, invite the vendors come in to show you. Make sure your business intelligence/data analysts participate to fully understand which data might optimize tools like automated lead scoring and decision journey optimization.
- Identify opportunities to get more out of the data you have. What insights can you glean that help you improve your content strategy, media mix, resource allocation, and customer experience?
- Content intelligence solutions pinpoint what topics resonate with your audience to help you build your editorial calendar, identify opportunities to address issues with tone or voice, and which content is most effective in engaging your users on social networks.
- Campaign management solutions can show you which tactics are or are not effective and recommend tweaks to optimize outcomes.
- Customer experience analysis tools show you where users experience pain points and which decision journeys are the most effective.
- Find tasks that can be automated intelligently. Anything that is repetitive, rote and currently manual is a candidate. For example, writers spend many hours generating fund commentary, market updates, and portfolio analysis that can be drafted with natural language generation solutions. Media management includes many boring tasks like media buying, targeting, testing and cross-channel management that can be automated with AI solutions.
Getting started with AI isn’t a choice for modern marketers. It’s a competency you can build immediately using the technology stacks and data in which you’ve already invested.
Asset Management, Research, Analytics, and Consulting