Spending the last 15 years’ working with top-tier and challenger financial services and property brands, Allie Moxon is a marketing communications consultant. She focuses on meaningfully connecting brands with their target market by creating awareness, building out marketing technology capabilities and delivering personalisation at scale.
Qualified in journalism and commerce, Allie specialises in content and digital; two marketing functions at the forefront of AI disruption, and so we took the opportunity to sit down with her and discuss all things AI!
Q. Parity: AI is revolutionising the way every business operates and no function is immune! In your opinion, how is AI changing marketing as we know it?
"We are entering an era where building share of voice and capturing customer attention will become even more competitive. Many businesses are starting to use AI to produce more content. It won’t necessarily be good quality, or help brands authentically profile their people, but there will be more noise to compete with.
Great businesses will lean harder into personalisation capabilities at every touchpoint across the customer lifecycle. Strategic data management and sophisticated segmentation strategies fuelled by AI will become linchpins for cut through.
Companies should consider creating a roadmap for AI adoption across new and existing technologies that digitally engage with customers, or manage their data. Brands will need to learn when to automate their outreach with AI-driven personalisation and when to create opportunities to connect customers with 'higher value' human conversations. Capturing and managing data will become marketers biggest challenge over the next decade.
While there are teething issues, I expect to see a shift in how customers want 'low value' information delivered as adoption increases and the technology improves. Service must be personalised and immediate. Chat bots have become impressive when executed well for example. But when interacting with voice bots, I expect most of us have begged to speak to a human instead."
Q. Parity: What is the potential of the technology for organisations targeting large markets, or companies with complex products and services?
"Let’s talk about the personalisation capabilities that exist on the market today. You won’t believe what is already possible with CRM software that has integrated generative AI into its offering.
Right now, generative AI is capable of scanning your database for the people most likely to purchase your product or service. It can learn to craft personalised emails in your sales person or brand's tone of voice, based on real customer interactions, that with a single “approval” click from a human will be sent at the exact time your customer is most likely to open your email.
If you operate within a complex business category, the customisation capabilities are endless. Consider a business that sells managed investment products. You can teach the system to adopt a sympathetic and humble tone towards people who have lost 10%+ of their capital in your products in the last 12 months. You can tell it to remove these people from an acquisition marketing campaign promoting new products based on behavioural activity, instead building lists of people that know, and don’t know, about the weaker product performance. Right there, your system can prompt a human to consider meaningfully interacting with these engaged segments for retention purposes. It can create campaign landing pages in your branding in an instant.
Imagine you are working on a demand generation campaign for a global financial services business with complex compliance requirements. You can teach the system to only market products to eligible customers. It can translate your copy into several languages. You can teach it to consider laws and your specific licensing arrangements in different jurisdictions.
The possibilities are limitless. But don’t underestimate the amount of work (or cost) required to establish a capability this sophisticated. It could easily take 2-3 years' work in a larger organisation.
"Your output will only ever be as good as your data and how well you train and maintain your model."
Q. Parity: How do you assess whether a business is ready to make this leap?
"You need to frankly consider whether your business is well resourced to engage on a personal level with your target market, whether personalisation is needed to drive sales or great customer service in your category, and if you’re looking at moving forward, your organisational strengths and blockers.
You don’t need to do everything at once. Not every business will be an early adopter and we are still very much in an experimentation phase. Developing these capabilities can be staggered over a number of years if that suits your business.
Just don’t get left too far behind. You won’t be in a position to meet shifting consumer expectations driven by other brands, your agility and reach will be reduced and your employment brand will suffer.
Broadly speaking, we are in a cost-constrained business environment, and the investment required to get a sophisticated AI capability running is significant. Implementation and ongoing software licensing costs will get cheaper with time.
Adopting these capabilities will also increase your ongoing marketing and IT costs, in terms of both software subscriptions and costs of skilled labour. That said, AI is also capable of taking on the work of a team of people. It can free your people up to focus on more meaningful work.
I broadly advocate for housing your data with a top tier external CRM system provider instead of building a capability in house. Consider locking in arrangements over the medium term, but also consider the potential for disruption from new software entrants. You are outsourcing innovation and risk management, and these systems are priceless if they don’t fall within your core competencies.
Successful execution also relies on understanding your customers path to purchase and knowing when to introduce a human touch. Your sales and client service departments are an extension of your brand. I’ve seen individuals named as brand associations in third-party research surveys.
In complex, relationship-driven product categories, avoid making your outreach feel robotic at all costs. Your goal should be creating opportunities to nurture meaningful relationships during high value interactions and increasing speed and personalisation of service for lower value interactions."
Q. Parity: Allie, what are the biggest barriers to adoption in your opinion?
"Taking new capabilities to market and establishing the underlying marketing operations that support these activities is a cross-functional effort. Prompting, and contributing to the design of system frameworks or parameters, is a skill set gap that marketing, sales, client service, IT, compliance and legal teams will all need to learn to work through together. It’s a highly technical area.
There will be a large element of change management involved for any organisation, with some individuals resistant to shifting to digital ways of working or feeling broadly uncomfortable with AI replicating human activities.
"If change is not being driven from the top down, adoption will fail. Consider who drives ways of working and culture within your organisation. Forward-thinking leaders from each impacted department need to become an expert on how the technology relates to their function."
Consider whether people on your floor are using systems or spreadsheets. If there are several spreadsheets circulating at any given time, you have a significant data management problem and potential liabilities.
Dialogue around the benefits of reducing administration burdens and saving time, versus preserving the human side of relationship management and what it means to provide great service in an increasingly digital era will need to be explored."
Q. Parity: You’ve mentioned that managing data will become an even larger issue for companies to tackle. What can businesses do now if they are not ready to adopt?
"If you’re not looking to adopt right now, you need to be developing a roadmap for managing your data and identifying the skillsets you need to develop internally to move forward:
Start thinking about your sales cycle and the data points you can capture. Where can you create segments, separate low value automated outreach from high value prompted interactions with sales or client service teams, and what data points do you need to collect to support these?
Speak to your suppliers and assess what the systems you are using are capable of - and their technology roadmap. You may need to structure your data a certain way now. You may need to integrate several systems and data feeds, and look at providers capable of rapidly aligning automated data feeds with your database.
Think hard about what you don’t need so you don’t create manual work. Avoid capturing and retaining useless data, focusing instead on segmentation related data and behavioural data that signals active purchase intent or interest, or gives insight into a path to purchase or loss of a customer. Capture levels of customer satisfaction. Wherever possible, automate your data collection processes.
I call this “AI readiness”."
Parity: Very insightful! Thank you for your time Allie!
This AI Insights for Marketing & Digital Professionals article was brought to you by Vanessa Lalani at Parity Consulting.
Looking to hire Data, Marketing, Digital, Communications and Product professionals? Reach out to Vanessa HERE or 0410 001 819.