21.11.2017 | Marketing Technologies
We’ve collected experiences on hundreds of information management projects with our clients. And, since the more efficient use of data is on the agenda of most companies, we’ve put together some of the lessons we’ve learned.
In information management, the data you own is your most valuable asset. But, garbage in, garbage out, so it needs to be of good quality.
The bad quality of your data often comes as a surprise. There can be many reasons for this. There is no systematic way of collecting data, no process to support this, and no knowledge on what the data actually contains. Data is not harmonized and it is very difficult to do time-series analysis over longer periods of time. Data also lives in silos, so creating a holistic picture of it requires a lot of work.
Collecting the right data requires endurance. All advanced analytics projects require structured data over long periods of time. Also, marketing automation tools require analyzed data as an input.
The bad shape of the data is often discovered only when new systems or technologies are being implemented. New technology won’t forgive the data deficiencies. Even a simple data visualization project to build a dashboard can turn into a monster project because of bad data.
How good is your data? Data quality needs to be on your management team’s agenda today.
Increasing your customer insight or understanding the yield of your marketing activities can be a challenge if your data is in a bad shape.
Companies usually excel in collecting hard financial data. Data on sales and operating margin can be found easily and be rolled, for example, to product and customer level. Likewise, data on one’s own euro purchases is usually of good quality and comparable in the long term too. Companies typically collect sales data into some sort of a database, from which it can be used for visualizations and in analyses in an agile way.
However, CRM data is still surprisingly often out-of-date and it even lacks basic level cleansing or enrichment. And even more often, CRM data lacks specifics on the sales process itself: customer transactions, like meetings, offers and closings.
Marketing investment data seems to be in good shape, but everything else may be missing: exact timing of actions taken, number of contacts in various channels (including direct advertising and telephone selling), all digital data (e.g. ad impressions and clicks, web analytics) and customer marketing data (contacts, push% etc.). Cookie-level data from digital interactions with the existing and potential customers should also be something that every company collects.
The much hyped personalization, i.e. omnichannel-like tailoring of all the customer interactions across all the channels won’t work if the abovementioned data is not in shape.
Proper data management and governance requires persons in charge
If you have problems with data, the first thing to do is to appoint persons who take the responsibility for data management and governance. Two functional titles commonly used for these roles are Data Steward and Data Custodian. Simply put, Data Stewards are responsible for what is stored in a data field, while Data Custodians are responsible for the technical environment and database structures. After this we can start defining our business needs, available data sources, and start implementing the required processes and technologies for data collection, storage and visualization. We recommend collecting all your data into a single database and protect it well.
Besides data management and governance, resources must be allocated to smart data analysis and exploitation in your day-to-day activities.
If need be, you can find good partners from the markets to help you in your data management and governance projects. In many cases, for example, a large part of marketing data is available from partners, from which transfer to your own database is not a problem.
Finally, we are pleased to provide four tips that our clients have used to proceed with their own data projects:
In the very first stage, we recommend building simple processes for customer data management and governance and continuous enrichment of it with applicable business data. Don’t let your data decay and erode.
One of our smart clients ensured continuous updates by tying sales bonuses to CRM updates…
In case some valuable data is not in your company’s possession but sales data, say, stays in your retailers’ systems, you should ideate novel reasons for data sharing: how, for example, a retailer can benefit from the data being better analysed and used.
Non-current data can be partly ”fixed” afterwards. An expert analyst can, for example, reclassify data in an agile way.
The first step is the hardest but the work will pay off manyfold in the future. With high-quality data information management is not only verbiage but works as a valuable asset that appreciates over the years in your business development efforts.