In the age of “Big Data”, we’re seeing a strong focus on the way businesses gather, analyse and use data across various departments. For many of us gathering, verifying and extrapolating data is intimidating, even though we’ve probably been doing it for some time without even noticing it.
Building databases has been standard business practice for years. Building an email, mobile or customer database, for instance, is a common activity in business operations. Often these databases grow with a slow trickle of names, email addresses or billing details for years and are used effectively for one purpose or another (marketing, customer support, sales leads, etc.), but remain isolated for that one purpose. Just because the information is sitting there doesn’t mean that the company is getting optimal value from it. Many of these businesses have been overlooking the strategic value that data can provide.
Effective database management is highly reliant on competent tools and people. At some point databases are usually interacted with – updated – by people, and human error can significantly impact the quality of your data. However, even the best people and tools won’t necessarily give you the right data. Data is about information – how you gather it and how up to date it is will affect how effectively you can use it.
Here are some considerations when using your database as the foundation for your data strategy.
The value of your data is entirely reliant on how relevant it is to your business objectives. A crucial step many businesses miss when embarking on a new campaign or project is to first assess what the objective is, and then decide what data will be needed to track, monitor and assess the progress of the project, and ultimately achieve the objective.
This can be very broad, so I’m going to use the example of a customer database. Much of the information you would want to gather on customers would probably need to come directly from the source. This is best done on a drip irrigation basis: little bits at a time. Most of us get annoyed when a company expects us to fill out long forms or sit through ten minute phone conversations to answer seemingly irrelevant questions.
So, What Data Should You Look for?
Depending on your business, this could be anything including:
- Email address
- Mobile number
- Date of birth
- Date they were added to the database/opted in
- Date their information was last updated
Always keep it relevant to your business and don’t request or track data you can’t use. Think of your ideal marketing criteria – how would you dream of segmenting your database? How much of that information can you gather without having to interrupt the customer? Product information (what product or service they’ve bought from you) can easily be stored during the sales process, for instance.
Collating and Organising Your Data
Typically, you’ll find that a business has:
- A database (or several) – e.g. email, customer, or call centre databases.
- A point of sale system where further data on products purchased, average spend, etc. is stored.
- Various forms of Web data – from display or PPC networks, keyword research, site analytics, or social media or email marketing engagement metrics.
- Social media networks – your Twitter, Facebook or LinkedIn networks can also be considered databases of sorts.
Cross-comparing these databases can open up possibilities for new comparative analysis of various actions and metrics, providing room to experiment with new data combinations. Ultimately, this will either:
- Reveal areas where you may want to build out your data gathering; or
- Give you a much more integrated view of your business.
Often businesses find it easier to layer databases when they choose one as a central repository on which all the others may be layered. This means that, while all these databases may still function independently, there’s one central database that updates with the information from all these various other databases. While few companies have this as an automatic process, smart data businesses will usually ensure that all their databases have the functionality to integrate with this central repository when needed; either on an ad hoc basis, or for periodic data updates.
This will generally leave you with two central types of data: identifiable data (which can be linked to a particular account or person) and generic data (which gives insight into general processes and cycles, but cannot be linked to one particular point of contact).
Keeping It Fresh
Call it what you will, but “stale”, “outdated” or “unhealthy” data doesn’t benefit anyone. Yes, older data can help you assess trends over time – this is typically more effective with generic data, but identifiable, or customer data, is usually useless if not up to date. Maintaining a customer relationship when you don’t have valid contact details, for instance, is near impossible unless you put in a lot of timely effort to track the person down.
How Do You Keep Your Data Up to Date?
For generic data, continuous monitoring of trends and changes, and noting what causes these changes, is necessary. This is also useful in that, as your business evolves, it should also quickly make it clear when your data is lacking in a certain area. For instance, if you know that you generally receive increased website and store visits during December, but your sales drop, you know that you need to gather more data around your inventory and in-store environment during that time.
For identifiable data, bear in mind that updating data regularly effectively means you need to facilitate regular dialogue with those contacts on your database. Whether it’s through a call centre, an online prompt or a quick question at your in-store point of sale, there needs to be a plan for updating details at regular intervals.
These first steps in collating and managing the beginnings of your data approach will, more than likely, require changes in your operations, marketing or CRM activities. However, as Big Data trends tell us, when analysed effectively, it can become fundamental in informing your business strategy.