In my marketing and technology world, the insights delivered through data and analytics help brands to measure efficacy of a campaign, but also to understand their customers more intimately - tracking and capturing the right data at the appropriate point can yield business insights that can inform a range of different business and budgeting spend decisions - and it can enhance your customer's online experience.
Palesa Molukanele; Head of Data, Insights and Analytics at Wunderman Thompson
In recent times, we’ve witnessed how Covid has accelerated digital transformation. It only took about eight weeks for businesses and consumers to adopt digital ways of doing things, instead of what may have otherwise taken five years. Elderly people, who often refer to themselves as BBT’s (Born Before Technology), were suddenly opting for virtual consults with their doctors, fitness enthusiasts had to quickly adapt to home/online training when gyms suddenly closed, and companies like Discovery turned to rewarding customers by introducing programs like ‘Vitality at home’.
This pivot to enabling digital interactions brought with it a new focus on what we call the online user experience, but for many brands the lack of a digital strategy as part of their digital transformation has hampered a seamless user experience. It can not only damage perceptions of the brand, but it also has a bottom-line impact!
Data tagging on online platforms, and data capture through important stages of a customer journey like onboarding and application are key elements of such a data strategy. Not being able to capture and track user behaviour through data tagging and capture is a critical oversight – it leaves you with half a picture, and the major challenge of playing catch-up. It’s tough for businesses with legacy systems to compete with the frictionless sign-up and usage processes adopted by players like Uber and Netflix, and not having the right data will make it even tougher to compete and ultimately mature one’s offering.
A few months ago, I went through a frustrating process when I was purchasing an additional property. From printing, signing, and scanning back multiple, very similar forms to a financial institution I already have an existing mortgage bond with, to then having to sit in attorney’s offices, initialing each page on a deck of more than 100 pages. Wearing my consumer hat, I’m not really concerned about the operational processes of an organisation; if my data exists in one of the business units, I assume it should be able to be safely and securely shared wherever it’s required. Sadly, this is not generally the case…and it’s largely the result of tackling data capture in a fragmented manner, not appreciating the true value of that data, and failing to implement changes and upgrades to system in a manner that feeds an overall, holistic data strategy.
Privacy laws such as POPIA in SA dictate that organization’s only request necessary data to serve their users, so you may need to trim the detail you would have been able to capture in the past or introduce opt-ins on certain fields…but it’s no excuse for approaching data gathering, capturing and storing and sharing in a haphazard manner.
Working with my tech and e-commerce colleagues at Wunderman Thompson, we have developed a five-stage project approach to help our clients transform digital data capture in a way that supports an overall data strategy as part of a digital transformation vision. There are some key principles we find are crucial for success: We need to ‘be’ our own customer, see our products and services from their point-of-view, and gather data in a manner that follows a step-by-step intuitive logic – how we then gather and store that data is a backend process that should enable a single view of that customer. It’s about re-visiting the detail, e.g., de-duping fields requiring the same data points from users, or understanding which data you capture informs a sales trigger, or which one informs a CRM trigger, and so on.
Technology and software specialists need to be consulted to help standardize and simplify, but this process is not a pure tech-implementation. Digital strategy implementation entails collaboration between teams that specialise in different skillsets.
Appreciate that feeding the data that is captured from our customer-facing channels to our backend data repository, and then aligning across different databases that might exist as part of one’s legacy systems requires new tech, new systems, new workflows, new design, and new ways of working – change management is a critical success factor
Teething issues will always be a part of any data strategy implementation process, and one cannot discount that just as you feel the project has been successfully implemented, new ways of working and new compliance requirements are likely to evolve. Implementing a data is only the start of one aspect of a digital transformation; it should be seen as laying the foundation…
Improving the customer experience is by its very nature an iterative process that requires ironing out duplications and adding features that enhance that experience continually. If your partners in implementation have not had this kind of discussion with you, they’re seeing the project from an over-simplified perspective and chances, are you will have to duplicate some of the earlier stages and implementations all over again at a later stage…
Our philosophy is a simple one - get the behind-the-scenes ‘backend’ systems and data flows and process right, and the consumer-facing ‘frontend’ of your platform will automatically deliver a much better experience.
Finally, in my experience, if you are looking for help, ask for some upfront no-strings-attached audit work and get a clear picture of the data strategy project approach your supplier is proposing. We have done this with several of our clients, and we have found that it is a good way for all stakeholders to appreciate the inter-relatedness of various business units and teams on this kind of exercise. It is not a purely technology or IT exercise, it is not a purely marketing exercise, and it is not a purely design exercise – each play their part in laying the groundwork for successful data analytics that builds true business insights.