Mapping the Customer Journey
Covid-19 saw customer psychographics undergoing a sea change, with life going digital full swing. Naturally marketers were not left unaffected. Churn, retention, loyalty, purchase drivers — everything was disrupted.
At our customer and marketing analytics division, I’ve been trying to pool all the intellectual property we have delivered over the past decade into a set of customizable accelerators, through the year.
This spans a fairly complex and inter-woven set of sales, campaign, customer and marketing AI implementations. What was conspicuous by absence was a starting point and how the inter-linkages between these AI modules, and more importantly the benefit of such inter-linkages, could be made transparent to the CMO organizations we served.
The same persona employs a campaign analytics tool to check campaign and channel effectiveness, yet does not test uplifts nor studies market sentiment on different aspects?
Having experienced first-hand how a lot of organizations tend to focus on the immediate quick-win of AI rather than the overall strategic business impact of an end-to-end organizational AI design, I’ve felt the need to start with visualizing for my clients, this future end state, upfront.
Is a 10% additional MROI using an MMM and an Attribution Model the best AI can serve you? Or can you amplify this to a 40% ROI YoY by linking MMM, Attribution and Uplifts to Competitive Game Theory, Customer 720, Next Best Action, Market Sensing for New Product Development, Campaign simulations for real time strategy/tactics changes?
Strategic Marketing AI differs from OTC MarTech in that it isn’t a one-size-fits-all tool. Yet this isn’t a one-time implementation that needs continuous and repeated investments either. What we’ve created is a number of inter-linked and highly customizable accelerators that save clients time, cost, effort but are absolutlely specific to their unique business contexts.
The start of which involves drawing out a customer journey for each client. It is important to recognize the complexity of trailing, measuring and timely interventions to optimize customer journeys as they evolve through critical stages from awareness to advocacy.
A lot of study and interactions later we developed a customer journey template. As this is somewhat generic, our AI marketplace and consulting team bridge the gap wherever customization is required.
This template is used to run assessments of existing client initiatives, run maturity ranking, and then plug whatever gaps we find during our audits, with our 60+ Adaptive Marketing Analytics modules.
The process has helped us stay true to client budget considerations by leveraging their existing value created, as well as optimize and alleviate the CMO organization’s overall effectiveness.
In a couple of our success stories, we were able to create journeys that linked the marketing organization back to support, R&D as well as the CEO office.
Key takeaway from all these experiences has been to use AI in a way that optimizes business returns, not just the departmental returns.
