Powering Personalisation: Back to reason you started
I plan to use this series to write my experiences and thoughts of how putting people (your #customer) back at the centre of what you do will start to drive obvious but incredible new strategies.
Before we get into the technical aspects of #personalisation, what I believe is critical, is to re-establish why you do what you do? What problem were you originally trying to solve? What aspects are still broken? Fundamentally, how can you do a better job?
Somewhere between starting the business and where you are today the customer has been forgotten and the rise of other factors take priority. It’s important to recognise this and make that decision to #change and start to drive a different #culture.
Choosing the right partner
Let's get this out of the way... You might need help! There is a reason consultancy exists and it’s not just to bring someone in, pay them a check and let them tell you what you already knew! Good consultants will bring a new perspective in thoughts, skills, process and data that you didn’t previously have. If they aren’t doing this, they won’t be worth the check your cutting.
Marrying intent with the right campaign
Platforms like Google Marketing are great at helping you shape and distribute your messaging to the right device at the right time to the right person. But let’s go back one step, how are you identifying the right message? How can you be sure what you are messaging is #relevant and resonates? This is where your partner can become so valuable. If they have access to a wider data set, suddenly your ability to focus outside of just your organisation will open your eyes to a whole new world of opportunities. Opportunities you may not have realised even existed in your market. This is where you are able to marry the signals coming in from your marketing platform and align with the right opportunities in your market.
An intelligent competitive advantage
Going further, with wider data sets, opens the opportunity for greater #predictive insights that will be a lot more accurate than just using your slice of the market. For Machine learning (#ML) and Artificial intelligence (#AI) to really become a mainstream reality, better access to data is fundamental. Too many organisations are building trigger applications and calling it AI. Instead, use ML to identify the ’unseen’ data patterns, use this as inputs for training models to predict future outcomes that feed automatically into workflows to give you a truly intelligent competitive advantage. This level of automation is critical to realising success and a ROI that will create confidence in your organisation to push further on.
Having a data scientist will not transform you business
A new culture is required. One where current methods are challenged and a willingness to test, learn, fail new ways of working.
Failing, but failing quick needs to be encouraged. There is no standard playbook to AI, and that means your teams need to feel comfortable failing. It’s a cultural shift — you will not get these models and new approaches working straight away just because you now have a data scientist. Data scientists are there to prove or disprove a hypothesis, they need guiding and to be part of a wider commercial team that is determined to change. Going back to the original point — if you want to deliver a better level personalisation, your data scientists wont give you the answer they will be an enabler through the commercial team to make this a reality, this is why I’d encourage you to have them embedded in your customer-facing functional team’s and not alone in the technical world.
Getting stakeholders to appreciate their value and potential will only happen through commercial gains. This will have the added value of keeping the data scientist engaged and energised, keep them close to the outcome and the use cases.
You have a partner, you have the data and now a new culture
All that is left is to continue putting the customer first. Keep building products and services that delight your users. Measure every interaction, and test the alignment against your hypothesis. Never stop learning! When you learn that a process has failed, move on quickly, celebrate the lessons learnt and start a new exciting pivot.
Every customer is unique, which is why personalisation is so critical. But, it needs to be done in a way where the customers knows you understand them but still allows them the flexibility to feel like an individual.
Do a great job and show your customers you #care
A new conversation
I’d love to hear your thoughts. I still have a lot to learn and hope these articles only serve to start and stimulate a discussion.