continued from part 4
Connecting Data Sources:
Data sources independently can be very beneficial to a business and provide great insights, but connecting these sets can help a business rapidly adapt to its industry, users and potential threats and opportunities.
Connecting data is no mean feat. It requires a combination of technical knowledge of the systems used to collect the data and input from business departments as to which data can actually belong in a connected set.
In this case, you are merging apples and oranges to create a new superfruit, but you need it to look and taste good, not just be a merger of the two fruits.
Some examples of connected data sets could include:
- Email marketing system with CRM to create personalised and automated email marketing campaigns
- Facebook followers with e-commerce subscribers for remarketing of previously viewed products
- Triggers that identify users who previously visited your site, logged in and took an action that then creates a specific pop-up on a page with an offer
- Connecting Google Analytics, Facebook insights and Twitter insights data to aggregate demographic data and compare in a single view
The purpose of connected data is to increase the value of the collected data. If there is no inherent value in connecting specific data sets then rather focus on those that have immediate and usable value generation potential.
Understanding
Sometimes we listen to music in a foreign language because it is beautiful, touches our soul and inspires us. It is appealing to our emotions yet we don’t understand it. For all we know, the lyrics are the crudest and rude that you would ever hear. But we don’t care because it sounds good.
Many businesses do exactly this when it comes to their collected data. They look at it and basically say: “Well, it looks good…I think”.
When the first steps are missed in creating robust data, this is the result, a data set that everyone wanted but no one cared to actually understand. It became a process to be completed rather than a value-adding activity.
Having said this, data is not for everyone. It generally requires someone along the way to interpret it into a useful and understandable format. In business, these are usually your analysts. They will take the generated data and translate it into easy to understand and use reports and insights.
Again we stress that, if you do not an analyst in your organisation, taking the first steps would have been a waste of money because you cannot understand the collected data.
Application
Whenever we do a client strategy session we start with a circular diagram. This is because any good strategy in our modern world is not a straight line to completion but a continuous circle of learning.
This is even more pertinent to digital marketing and data. We use collected data to make better decisions which we then test, again and again, applying the process to increase return, reduce cost and maximise value.
However, at the end just before the cycle begins again is the application of learnings. Many businesses get to the point where they celebrate their amazing insights and then do nothing with them. The last step is the most important. Take everything you have done and start making greater returns.
If you learnt that your users prefer green shoes to yellow shoes then make more green shoes. It sounds simple, and it is when you don’t ignore it and create actionable outcomes and areas of responsibility in your organisation for these actions.
Summary:
You must be so tired after reading all this so we will keep it short.
- Data needs to be made useful;
- Useful data needs careful planning;
- Data needs specialists who can create, connect, interpret and apply;
- Always remember compliance;
The purpose of data is not just to see but to do. Don’t get to the end of the cycle and then stop. Apply, repeat, learn, adapt, apply…
Thanks for reading…..if you got here?
