Database Marketing Definition
Database marketing can be defined as the collection, analysis, and interpretation of customer data in order to drive more relevant customer experiences. Database marketing involves the collection of data from a range of sources including customer email correspondence, CRM system customer info, data warehouses, and, increasingly, external sources like social media.
Database marketing can be used for communications with current and potential customers. With so much customer data – both internal and external – available to companies today, database marketing is becoming an increasingly important part of the overall marketing strategy.
Database Marketing Examples
The modern customer expects personalized and highly relevant communications with your company. Any materials that seem generic or irrelevant will quickly be skipped over. It is vital that companies engage with customers about the issues most pressing to their business. Database marketing techniques can inform companies of their customer needs and can be the foundation on which to build successful marketing campaigns.
Companies today use database marketing in a number of different ways:
- Listening: Leveraging a range of external data sources like social media, company news alerts, personnel changes, database marketers can pinpoint the most suitable companies to target for their next marketing campaign. Other data points including socio-demographic info, product preferences, and digital behavior can also be collected to create a complete view of your customer.
- Relevant Communications: By developing a complete customer profile, database marketing enables companies to deliver the right message, at the right time, to the right person. By analyzing up real-time data sources like social media, database marketers can seize upon opportunities as soon as they arise and deliver the most intelligent and targeted marketing communications to both potential and existing customers.
- Customer Retention Offers: Database marketing can help your company increase their retention rates and loyalty, by delivering the most personalized retention offers which take into account factors like digital behavior and online transactions as well as socio-demographic and location data.
Challenges of Database Marketing
- Heightened Customer Expectations: The ubiquity of Google search and the smartphone has given today’s customer instant access to the world’s information. The impact of this access is that attention spans have shortened and customers can also find out quite a lot about your company before they ever engage with any sales reps or marketers. As a result, marketers in the past might have shared company brochures with potential customers, whereas now any materials that do not deal directly with the customer’s business needs will be immediately dismissed as generic. In order to meet these heightened expectations, companies need to deliver highly personalized, relevant, and well-timed marketing campaigns and customer interactions.
- Data, Data and More Data: Companies today store incredible amounts of data. Add to this all the external data points companies can leverage like digital behavior and preferences, and then you begin to get some idea about the sheer scale of the data available. Interpreting and analyzing all this data is no longer humanly possible, so the most progressive companies are turning towards customer experience technologies which capture data across all these channels and generate the contextually relevant insights companies need to resonate with the modern customer.
Database Marketing Best Practices
When it comes to database marketing, there are a number of best practices companies can follow to give them the best chance of succeeding.
- Multi-channel marketing: Customers today no longer operate on a single device. For example, they might begin looking at your product on their laptop and continue their research the following day on the train on the way to work on their smartphone. Finally, they might check in again on their iPad later that evening. For your database marketing campaign to succeed, you should strive to provide a consistent customer experience across all devices. Users should be able to switch device without any disruption.
- Analyze All Data Streams and Sources: The best customer experience tools analyze the data that takes place across your entire technology stack and all your data streams. It is vital that you gather all this data and not just some of it. In order to get a complete picture of your customer, you should look towards tools that analyze data from all available sources like CRM systems, data lakes, online behavior, and POS systems.
- Predictive Analytics: With so much data available to companies, database marketers who choose the right tools can leverage predictive analytics which push alerts and notifications to users at the most opportune moments in the buyer’s journey like when a customer looks like they might discontinue service. These insights can help your company eliminate issues before they arise and drive loyalty in current customers.
Turn data into insights with Customer DNA
With our Customer DNA, you are not dependent on predefined flows or metrics. And even though some Standard DNA metrics could be interesting for certain industries, data is too business-specific to generalize this. That is why everything is fully customizable to your business needs. Easily define custom metrics using various methods including formulas, predictive models, neural network models, linear models, and more.
Relevant experiences drive customer engagement. You can’t make a connection with your customers merely based on that data. Beyond standard customer data aggregations, you need meta information about products, offers, context variables, etc., to continuously score that customer’s propensity or eligibility for converting.
This strong combination of meta- and context information and model scoring is where our Customer DNA differs from others, as we go beyond the standard digital customer info.
Further Reading on Database Marketing: