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Creating Value: Know What You Are Building

Know What You Are Building

Introduction

You know that you need data. You know that data can help to improve decision-making, increase efficiency and get you close to your customers. But where should you start? Businesses by their very nature are complex things, with each department having their own unique challenges, so how can data help you address them, what technology will you need and where should you start?

Data Is Not A Silver Bullet

While we know firsthand the huge impact that data can have on an organisation, it is not a magic solution to every problem! In order to create value from data it needs to be closely aligned with your business problems and decision-making processes. If your data is not relevant or aligned with this and if there is a lack of engagement from the team in utilising your data tools, the potential benefits diminish significantly. Data becomes another background report that will not affect change. As such, while data is a powerful asset, its effectiveness depends on the context, usage, and the overall data strategy of the business.

So Where Do You Start?

For most companies a ‘data-driven culture’ is a change from the norm, even now. And where there’s change, there needs to be management. This means that before you do anything, you need internal support from the c-suite, a project leader and a clear outcome. 

With this mandate, the first thing you should concentrate on is not data at all, but understanding your business priorities and problems. This can be a difficult thing to unpick as no doubt each department and each person has a different viewpoint on which data would be useful, and where the issues lie today. This is why we often find that a better framework in which to organise these conversations is to first consider your customer journey.

Customer Journey Mapping

Most customers will go through a similar journey of: 

Acquisition – In which they become aware of your company and engage with your marketing. 

Conversion – The process in which they actually become a customer either through making a purchase or signing up to a subscription. 

Lifetime value – In which you try and retain and grow your profit from that customer. 

Each of these different phases will have different touchpoints associated with it, and normally different teams. At the acquisition stage customers might interact with you through social media or advertising for example, at conversion they might come through your website, afterwards maybe you will use your CRM to track your communication with them. With this plotted out it should be easier for you to unpick the key questions along the pipeline. For example, if marketing spends a lot of time contacting customers so as to retain them, do they know which customers are more valuable than others? Maybe that info sits with finance in a different system and so by combining that data, they can understand which customers to spend time with. When asking your different departments about their data usage consider three key questions:

  • What data sources (website, tools, documents) do they rely on?
  • Do they trust the numbers they get from that data?
  • What key decisions do they need to make using that data and how often?

This will give you a great top-level understanding of where data can help, which data sources are used most often (and therefore are more important) and any issues today with trust. Check out our full article here for more details on how you could go about this.

Next Consider Your Technical Needs

With a sound understanding  of your business needs, consider the technical side. You should think about:

Data Volumes: To come up with an estimate, you should think about a good proxy metric, this is a value (or values) that give you an idea of the total number of records your analytics system will have to deal with. Which good proxy metric will depend on your type of business: number of orders would be a good predictor for an eCommerce business; number of registrations and active users for a social network. Try to think of what your customers are doing on your platform and how many actions (events) will be produced to arrive at a good estimate. The more events, the higher the cost.

Existing Tech System: Your data infrastructure is an extension of your existing tech setup. As such you should consider the tools you are already using, the skillset within the team and  explore potential benefits staying within the same service provider, for example, better compatibility and simplified billing if you stay within the Microsoft or Amazon suite of products.

Security & Data Privacy: You might also have specific requirements for compliance and data privacy. Most tools will provide details on how they meet regulatory standards such as GDPR, HIPAA or CCPA.

Cost: Your data volume and usage will continue to grow as your business and data capabilities expand. Cost and scalability is one of the top concerns we hear from founders and CTOs. When estimating tool costs, you need the following information ready: current number of records (total, new and updates), projected growth with existing data sources and potential new ones, and expected reporting usage today and in the future. Whilst many data tools have a free level of service which might be great for today, your data volumes are only going to grow and so it’s best to consider how big a leap it would be should you need to upgrade. There last cost factor is in hiring your data team which we will talk about in the next blog.

For a more detailed look at factors you should consider when designing a data stack, check out our blog here.

Conclusion

As you can see, there is a lot of work that needs to be done before you start delving into which data tools and setup you need. Ensuring you have clear outcomes from a business side is absolutely crucial, but with this in hand 173tech’s data strategy review might be useful. Here we help you to match those business requirements with the right data tools and give you a detailed roadmap to implementation- focused around value-creation from data initiatives. Get in touch with our friendly team to see how we can help.

Find out more here.

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