The Pillars of Personalisation
Discover how the Pillars of Personalisation propel us along the Analytics Maturity Curve. Through a Risk and Readiness Review, we assess Analytics Maturity, Data as a Resource, and Tools and Technology.
Explore their relationship to our Ferrari analogy, ensuring a memorable and comprehensive understanding of this framework. Unleash the power of personalisation and fuel your path to Analytics Maturity.
5.1 – The Parthenon to Sustainable Growth
Source: McKTui Consulting
There are three critical pillars required for effective and sustainable personalisation, and our data and personalisation strategies rest upon these foundational pillars. Each is equally important, although additional capability in one area can compensate for lack of capability in another. Like the Parthenon, without all the pillars in place, the structure, in this case your marketing growth and personalisation strategies, will be unstable. If we lack in an area, we’ll find it impossible to get any personalisation project off the ground at all.
To explain this memorably, let’s crowbar in another metaphor here. Think of a car; the car is a brand-new Ferrari. It’s a Ferrari because everyone knows a Ferrari is fast, powerful, and effective at what it is designed to do. Hopefully, your strategies do not cost the same as a Ferrari.
OK, so you have a Ferrari. It’s fantastic, with all the bells and whistles. It goes 218 miles per hour and has leather seats and an infrared cigarette lighter. For our sake, this could be a fully-implemented CDP, CRM system, Webtools, real-time recording of users’ sessions, directly accessible by a call centre, advanced self-service dashboards connected to all our customer and business data – and there is lots of data, fantastic data all expertly linked by a federated ID, with very little data loss and full permissions. You’re revving, raring and ready to go.
What do you do? How do you do it? Where do you go? Do you try four things simultaneously in an attempt to appease everyone else sitting in the car? Do you try to pursue the recommendations from the CEO’s daughter or be influenced by just the highest-paid person’s opinion (HIPPO)? Analytics maturity, as we’ve reviewed, covers many different areas, but most of them are centred around having the right people and process with the knowledge, skills, and abilities (KSA) to ensure that we take the optimal path and make solid, informed strategic decisions; otherwise, we are going to waste a lot of time and money; not only that, we could do more damage than good to the brand.
Source: McKTui Consulting
Tools and Drivers – No Fuel
OK, here is an alternative: you have all the tools, the Ferrari is still ready to go, and now you know what to do with it; Mario Andretti (arguably the best racing car driver of all time) is sitting behind the wheel with a full pit crew, and everyone is aligned – now that’s exciting and the sky’s the limit. But then you realise you’ve got no fuel; pretty impressive how you missed it, but the tank is full of a mixture of tar and gravy, and all the data coming in is junk. Some could be refined, but it is useless and flawed for your purposes.
Most likely, if you had the team worked up to higher levels of analytics maturity, you would not have made it to this stage of development. Still, it could be that you have lost your key data sources to recent legal or social changes, or perhaps you paid other organisations for their time in implementing your stack and their time as an extension of your team and didn’t stop to ask what you are going to do with this technology and what data you need to be collecting to get there.
You’ve got a fancy Ferrari, an expert team, and a driver without the data it needs to run. This could be particularly true if your company invested heavily in programmatic and DMPs, which traditionally required vast amounts of freely available third-party data to be effective.
Drivers and Fuel – No Tools
Finally, and this is the most exciting prospect for any SaaS salesperson, you have loads of great data and the in-house experience to understand what their product does and how to use it. You’ve got a pit team of Ferrari enthusiasts ready to go and some rich, exciting data ready to be used and integrated, with customers waiting to hear from you and willing for you to use their data.
In reality, it will never be entirely just one of these situations. Still, the model gives an easy way for us to explain and understand the different areas required to move forward, what could happen, and why we need to improve in one of the pillars somehow.
A good start for any organisation is to pull the various siloed stakeholders together and work through a Risk and Readiness Review. This could be a series of meetings or, ideally, a facilitated workshop to get the most out of your team. By evaluating your cross-functional teams, you can gauge where you are in each pillar and where to invest resources first. Follow-up sessions can be conducted after any initial investment in tools, data, or people to assess progress or as part of an annual or monthly cycle. By taking an initial benchmark before you start and having structured reviews, you can reassess and track your progress together and discuss any trouble areas or unexpected issues.
