Do you want to create a data-driven enterprise? Well, there are some fundamental steps you need to take on your Data Journey in order to get there. Here is our guide on how to do it.
1. Landscape Analysis
Before you embark on any new project you need to know where you are and what you have now. A Landscape Analysis is an audit of all your data stores to assess data quality, relationships, business rules and accessibility. From here, you can accurately scope the work ahead. Whatever stage of the Data Journey you believe you are at, you should always begin with a Landscape Analysis.
2. Extract, Transform, Load (ETL)
ETL is the process of moving data around your organisation to ensure it’s accessible where and when it’s needed. It’s important to build an ETL framework that incorporates data quality rules and processes. Make sure you select the tool that’s right for you and your team and consider what training you might need around this.
3. Data Quality
An essential element throughout your Data Journey is data quality. Ignore it at your peril! Define the rules that govern the data and embed them into your processes. We recommend creating a data governance board and data quality programme to manage this. Also, be prepared to deal with the exceptions that will almost definitely crop up.
4. Data Storage
You probably have more data sources now than ever before and you need to bring them together. You need to consider what type of data you have, where you need it and how often it needs to be accessed. This is often where a Modern Data Warehouse comes in.
5. Insight & Analysis
By this point in your Data Journey, you should have high-quality data in an accessible place. It’s time to use it! Using the data you can identify revenue-generating trends and target the right people in your audience for specific campaigns. Again, don’t forget to consider the skillsets needed to make the most of these tools at this point in your journey. Does your team need any additional training?
6. Campaign Orchestration
Want to build an automated welcome journey for a new customer? A stock re-order automation? Or a fault alert? Now you can. There are plenty of tools out there to help you automate and personalise your communications, across multiple channels. For example, Apteco’s PeopleStage is a great tool for creating sophisticated trigger-based customer journeys for an excellent user experience.
How do you know how well your campaigns are doing or how well you are performing? It’s essential to measure and continually monitor the key performance indicators for each campaign, using dashboards or creating reports that are automated, distributed and are easily accessible and interactive. While there are many tools available, we like Sisense as a flexible and innovative reporting platform with a high level of capability to suit any need.
8. Machine Learning
Machine Learning is the process of understanding what has happened in the past and using this information to predict what will happen in the future, through the use of algorithms. It can help you spot trends in your data, such as buying patterns, so you can capitalise on opportunities as they arise. Using Machine Learning to its full extent does require specialist skills, but it could be well worth the investment.
9. Artificial Intelligence
The ultimate in automated analysis and response. This is deep learning to build human-like responses. If you have followed all the above points to establish the right processes, infrastructure, tools, and skillsets, you are now in a position to explore AI. As well as simply predicting what will happen, AI enables you to take action based on this knowledge. The possibilities for you are now very exciting!
Want to know more? Get in touch.
We recently worked with Parkinson’s UK to improve their data quality and help inform the data architecture….
Poor quality data can affect many different areas of your business. Efficiency can be stifled, reporting inaccurate,…
If you’re not already using marketing automation of some sort, you should be. And here’s why. …