Understanding your customer’s needs and how they want to communicate with you is key to a successful marketing campaign. But, with huge volumes of data from multiple sources flooding your organisation every day, making sense of it can be a challenge. This is where Modern Data Warehouses (MDW) can help in marketing.
What is a Modern Data Warehouse?
A Modern Data Warehouse is a hub for accessing and storing data. It allows each application in your business, to access the same data regardless of format. This provides you with a single source of truth, at a single point in time. But how can it benefit marketers?
1. Improved accessibility and insight
If you store data in silos in your organisation, users can only access part of the story. This can limit decision making and lead to conflicts between departments. Once you’ve established your integrations, a Modern Data Warehouse collates, reformats, and analyses data in near real-time. This then provides you (and the broader business) with a ‘single version of truth’ to base decisions upon. With punctual and accurate data, you can gain deeper insights into your customer and prospect base. This, of course, means you can respond more effectively to their needs.
2. A personalised, omnichannel experience
The customer journey is becoming increasingly sophisticated, as customers typically interact with multiple data points. For example, a customer may first contact your company on social media, then talk via chatbot, before picking up the phone. This is a great experience for the customer. However, since each channel is managed separately it is usually very challenging to keep track of the customer’s different interactions. This is where a MDW can help. A MDW collects the data generated by all these sources, formats it, and makes it available to you. This helps you to understand customer preferences within individual journeys and create a seamless omnichannel experience. Enabling you to deliver the right content, at the right time, in the right way.
3. Customer centric
A Modern Data Warehouse can help you understand how your customers are interacting with you. It can give you a quick and simple picture of their behaviour, engagement and even satisfaction. The Business Intelligence (BI) insights you gather with your Data Warehouse can be used to predict future customer behaviour. For example, you could gather buying preferences and combining this with demographic information. This allows you to build a picture of how the customer may behave in the future, including their propensity to buy, meaning you can create highly targeted marketing campaigns.
4. Decreases risk
Because a MDW pulls data from a broad range of sources, it can be used as a central monitoring platform. That way, if the data starts to look odd, you can often intervene before catastrophe strikes. As marketers, being aware of and preparing for potential problems and opportunities can help you react quickly to adapt strategies and activities to put you one step ahead of your competitors. As the Covid-19 pandemic has demonstrated, the ability to pivot quickly and effectively is paramount.
5. Improves data accuracy
Every benefit we’ve discussed so far is only going to work well if your data is accurate. Opting for a MDW brings with it a whole bunch of data governance tools to help you make sure your data is accurate and can be trusted. For instance, you want to make sure there are no duplicates, that all the email addresses in your database are accurate, and that data retention policies are being followed automatically.
For example, if you don’t have someone’s first name stored, your amazing new personlised email is not going to have the effect it should. Or, if you have duplicates, it is going to be very difficult to offer an omnichannel experience for that customer when your system thinks there are two different people browsing your website and receiving emails.
6. Saves money
CRMs are great, and we wouldn’t ever tell you to stop using your CRM. But, if you are using your CRM to store all of your customer data, you can run into some pretty high storage charges. Using a MDW as a single point of truth, and then integrating your CRM is a much better way to work. Take Microsoft Dynamics 365, for instance, once you go above 500,000 contacts it begins to cost significantly less to store your data in a MDW.
Another money-saving tip about Modern Data Warehouses is that you are generally only charged for accessing your data, rather than storing it. So, if there are contacts sitting in your database that are very rarely used, you could even save money on paying for these while they are just sitting there not being accessed. Compared to storing those same customers on a CRM, this could be much cheaper.
While a MDW can make marketing quicker, easier, and more effective, the benefits are not exclusive only to marketing. By making a wide variety of data accessible to the whole organisation from a single source, it also reduces data complexity, improves decision making across the organisation, and can even help with crucial business planning. And, while the concept of an MDW is often shrouded in technical jargon, it doesn’t actually require your team to have any specific technical skills to get the full benefit from it. For more information on managing and delivering data effectively to support marketing campaigns, take a look at our whitepaper.
Modern Data Warehouses (MDW) have been around for years, but they have not always been very accessible. In the past, data warehouses tended to be highly technical and only seen as an operational tool. Because of this, you usually needed a data scientist or someone with technical skills to develop, implement and then manage it.
What happens when data migration goes wrong? We’ve recently seen some very large-scale failures that should act as a warning for any company planning to move data. Only last year TSB customers were locked out of their accounts due to the unsuccessful migration of customer data. The ramifications are still being felt.
Applying best practice is critical. Our recommended approach to data migration is a simplification of the Johnny Morris model, which is split into four different stages; discover, design, test and deliver. In this blog, we’ll take a look at how to get the first two stages right.