It seems like everyone is searching for ‘best practice’ these days. We are constantly looking to learn from what is being held up as good, leading and perhaps even the best itself. While this is a valid exercise, I believe we are missing an opportunity to take a closer look at ‘bad practice’. That’s when either people, processes or technologies create a scenario in which the business case doesn’t hold true and where the project – or parts of the project – eventually fails.
However, we really should take that opportunity because there are important, valuable and very tangible lessons to take away from most such cases.
1. Avoid approaching a one-to-one customer engagement project as a data integration exercise
Building a data-structure that supports the organisation learning about customers’ interactions, responses and preferences over time is a data integration discipline, but the initial approach needs to avoid looking at it that way. It might be that the organisation has 50 different systems with customer and market data in them, but the incremental value of integrating the last 45 of them might not be very significant and only hold very little competitive advantage. I’ve seen organisations spend 12 to 18 months on data preparation and data design but by the time their communication actually hits the channels, things have almost certainly changed. The customer might have new priorities and competitive forces could have shifted.
So my advice is – spend time thoroughly understanding where the valuable use case and competitive differentiation is and build the data processes, the analytics and the automation to address your highest priority use case. Doing so will get to a business outcome much faster. Moreover, it makes it much easier to ask for additional funding to add new data sources, new channels and grow your model’s maturity.
2. Don’t overlook or underestimate how data-driven customer engagement impacts your current way of working
Tailoring emphasis and investment to an analytical way of going to market is easy in theory but hard in practice. Intelligent, real-time recommendations to point-of-sale systems or call centres are only smart if they are being actioned. Call centre workers are not marketers and the churn rate in such teams is often high. So work with them and ask for their input as to how offers and service messages should be served in order to make their everyday life easier. Ask what they think could create a better customer experience in their customer touchpoints. This will not only refine your requirements, but will also start the much required change-management process at an earlier stage.
Take the same approach when aspiring to analytically optimise customer contacts – right message, at the right time – you know the mantra…Recognise that optimising won’t work at all if the business process is designed in a way that has brand managers or branch executives assigned to groups of leads/customers to market themselves to by the beginning of the month or quarter.
3. Don’t focus on functions and features before balancing them against a solid understanding of the implementation team’s skills and experience
Having been through buying cycles, implementation projects and even business-as-usual states a few times now, it always strikes me how much time and effort an organisation will invest in a near-FBI-style interrogation of functions and features when they are choosing systems to drive their multi-channel customer engagements. I’m not saying functions and features aren’t important, but the weight buyers attach to them needs to be balanced against a thorough understanding of the people and skills their vendors can provide in order to deploy and support the software in a timely and high-quality fashion.
As with my ‘overlooking’ and ‘underestimating’ point above – the days are long gone when marketing was just nice to have and ‘so be it’ if campaigns got delayed a little. If marketing is critical in driving tangible sales and customer experience outcomes then systems selection and implementation require a close relationship with the software vendor/system integration partner. This will ensure the business implements the right functions and features it needs within the right time and of the right quality.