Modern organisations are drowning in data. There is data everywhere. Raw data, transformed data, old data, new data, wrong data, right data. I’m not saying we have too much data; it may simply be that we’re drowning because we don’t always have the right data in the right place. Its the difference between having a burst pipe in the bathroom and a nice hot shower; It’s still water but one’s a problem the other a pleasure. A while ago I wrote a teasing and slightly provocative article. In the article I was critical of the efforts of programmes pursuing the concept of a single customer view (SCV) where if it was not clear what the definition of SCV was then SCV programmes would struggle. My perspectives still remain but I want to expand on a number of points to deal with technology changes that make SCV or CVM style programmes more challenging and yet at the same time potentially more rewarding. According to Bernadette Jiwa data is there to do three things:
- Confirm or disprove what you were already thinking.
- Make you ask more of the right questions.
- Cause you to act on what you discover.
It’s a nice simple way of looking at the role of data in your organisation. I’d like to tweak the three bullets for the sake of this article. My perspective is that customer data (for that is what I know about) is used in three ways
- To support operational effectiveness,
- To provide rich analytics
- and Enable informed decision support.
None of the above are mutually exclusive; far from it. I’d suggest that they are a hierarchy; the one after requires the one before. So if these aspects all work together and depend upon each other then the focus of your SCV programme will determine the shape of your activity, your architecture and your programme solutions. Misalignment of CVM programme objectives with approach is a significant risk. I’d also go as far to suggest that if you are embarking on a programme to develop rich customer decisioning and analytics capabilities yet your operational customer processes are blocked by poor data and poor data flows then that programme is at real risk. I’ll expand.
If you google “single customer view maturity model” you get a lot (and I mean a lot) of pictures on customer experience maturity; close but no cigar just yet. These pictures look at macro level efforts for creating leading customer experience (I’d go as far to argue they are too marketing oriented as well). And if you search for “customer data maturity model” you get closer (I quite like this one from IBM) but still I’m not sure. I’d go as far to suggest that it’s because we try to treat customer data in the same way we treat other forms of company data. I’d really like to hear what others think as this is just my perspective (but I do use it to inform my SCV approaches with clients). Customer data is not the same; in one big fat way. We don’t create it and we curate it at our peril. Controversy for effect I’ll admit. Customer data is like the water supply in your home. It’s presence is vital for a happy existence but if it’s not there in the right place and at the right time then that’s no good at all. It get’s piped in by a 3rd party and the only choice you have to make is where and how you use it. This analogy may work so let’s stick with it for a while and see how it goes.
Understand where you want to go
Here’s a picture. One axis describes the role that data plays in your decision making process. The other axis describes the point at which the decision is made (either during the customer buying process or outside of it)
As you can see in the picture your destination (or destinations) has options. An offline complete data set to support decision making is not the same as a more limited data set delivered to channels to support automated marketing response cycles or web personalisation. All may be appropriate places to go (and you can go to all of them). You may not be able to go to all of them at the same time. Set a roadmap or at least a broad indication of what your journey will look like through the matrix.
[stextbox id=”info”]Not all of our stakeholders understand CVM, SCV in the same degree of detail. Sometimes it’s really useful to be able to describe a complex change programme in simple ways. I think the above matrix helps do that. You can plot your own map points depending on what specific actitivies are underway for your business.[/stextbox]
Focus on customer data that delivers operational effectivenss
At the foundation level our use and management of customer data must be about to ensure operational effectiveness; that the wheels turn smoothly in our customer facing processes. This is really about getting the basics right. And about making sure they stay right. Really simple stuff; customer contact data, sales information, receipts, subscriptions, renewals, addresses, demographics, contact activity etc. etc. When stuff like this is wrong then things start to get very bumpy. In this data accuracy is everything.
Customers create your data
Data is created (much of which is by customers or 3rd parties in this day and age) and curated then consumed. The more channels you have, the more teams you have the more this simple cycle places your data accuracy at risk. The data flows around the organisation for consumption possibly including additional transformation (not structured curation). As it flows around the business it can get caught in backwaters where the data goes stagnant (stuck on excel sheets on peoples local machines), it gets cut off from the creation and curation cycle. So ensuring that the flow of data from customers (who create the data) to consumers (who make decisions about the data) needs to be as efficient and smooth as possible. So for me I recommend the following activities
Understand what customer data you have – where it starts and where it ends. I don’t propose a detailed deep dive of data structures and models (that would come later). This is more of a high level design. A circuit diagram if you like.
[stextbox id=”info”]Workshop with stakeholders to understand the creation, curation, consumption cycle and start to pick out the blockers and problem areas. Knowing where these are will come in very very useful later on. Map the processes at a high level and annotate your high level processes with ideas, issues, pain points etc.[/stextbox]
Prioritise customer data that is foundational to analytic capability
Once again it’s pretty simple (or maybe that’s me). Understand the big questions you want to answer (who is buying, what do they buy, when do they buy). Once you have answers to the big questions the other questions that follow are much easier to respond to. Likewise, the history of data usage in your organisation will determine what is immediately available, what requires work or transformation and what simply does not exist. Understanding the decisioning cycles and processes people want to have in place will help define the data that you’ll need. Purchase history by SKU, volume, frequency will align with demographics and other segment data.
Get the data in the right place
You’ll want data in a number of places depending on how you are going to use it. Data architectures, integration methods and the supporting Big Data capabilities are worthy of many articles on their own. If you understand how your journey through the roadmap will take place this will help set your information architecture priorities.
There will come a point when your degree of single customer maturity will firstly allow you to make point of sale decisions based upon your rich data set but you’ll also be able to adjust in realtime the decision making process. Some customers may be right for upselling/cross-selling one day. The next day for different reasons it may be a new set of customers.
Don’t forget the customer in all this
If you have the right data in the right place I’m sure it’s going to be put to good use. But don’t forget that customers can equally make use of the data you have to make informed decisions about how and where they do business with you (push notifications of renewals, bolt on offers, price changes, booking histories). Factor in how the data you have can be used to good effect by your customers. Serving the right data through digital channels can have a positive operational impact
Once again it’s a simple saying – the right data, in the right place, at the right time. And at the heart of it all is that as data is a constantly evolving and adpating entity within the organisation. It’s very hard to say at any point that a SCV is complete; that somehow no more needs to be done. The boundaries are constantly shifting. Folding in data from new social channels, removing data from retiring product/service lines. There’s no end to it. It needs to be a process or habit in itself to maintain (like pruning a fast growing tree). If the SCV gets out of lock step with the operational activities then problems arise in terms of accuracy and effectiveness.