Authored by: Geoff Soon, Managing Director, South Asia, Snowflake
Virtually every marketing organisation is taking steps to become more data-driven, but there are considerable gaps between vision and reality. CMOs and marketers are realising the value of using data and derived insights to truly demonstrate how they are accomplishing their business goals. Meanwhile, customer data complexity is only increasing. Organisations need to move beyond reporting inputs and outputs to showcase outcomes and telling stories. As the marketing industry calls for human connection stories, they need to work with the CIO and CTO to enable data collection and analysis that better reflects the human experience.
Here are some strategies organisations can use in order to achieve data-driven marketing.
1. Develop a comprehensive data strategy
Even as marketing organisations increase their spend on data and analytics, many do not have a comprehensive strategy. Instead, they leverage ad hoc, loosely coupled systems in an effort to infuse data into their operations. Additionally, buckets of data remain in separate silos and cannot be accessed or queried in real-time for better and faster results.
Here are three areas a data strategy should address:
People: For marketing data management to be sophisticated, organisations need to recruit data scientists and analysts who are highly skilled at distilling insights from data, as well as IT managers to make customer data available to those individuals.
Objectives: Which users need access to data, what are they trying to achieve, and how will the success of data-driven initiatives be measured?
Technology: Marketing organisations need clarity on the storage, security, and accessibility requirements to support their intended data use cases. They also need to determine whether to build their own data platform or buy an out-of-the-box solution to activate their customer data.
2. Identify which data sources are needed and how to ingest them
By zeroing in on the marketing data sources required to advance specific objectives, companies can avoid the complexity and expense they might incur by grappling with more data than they need. For example, companies may not need to ingest clickstream data from Google Analytics if they are using Adobe Analytics as the source of truth for website behaviour.
Some customer data, such as purchase history, is stored in internal databases, but most data needs to be ingested from its original source. To avoid burdening engineers with ongoing data maintenance, marketing organisations need an ETL (extract, transform, load) tool with prebuilt connectors to data sources. These solutions extract data from the original source, clean or change it into a useful form for the company’s purposes, and load it into the company’s choice of storage.
3. Unify data to create a single source of truth
Once marketing data sets are ingested, the data needs to be stored in a single platform that can natively support both semi-structured and structured data. Its infrastructure needs to be sufficiently flexible and scalable to enable near real-time data integration. It also needs to provide a single source of truth in the form of clean, merged data sets that a variety of teams can use.
The solution is a platform that can instantly scale up capacity to deliver more computing power on demand, freeing up teams to produce outputs as quickly as they can. Instant elasticity removes scheduling and data batching concerns, letting data scientists run complex models and enabling non-technical users to access dashboards whenever they need to, with no “noisy neighbour” challenges.
4. Make data available to non-technical users across functions
To unleash the full return on investment (ROI) of their platform, companies need to think beyond the productivity of data scientists. The platform should be accessible to a large cohort of less-technical users across business functions, including Marketing, Operations, Compliance and Business Development.
If a platform is to cover a range of use cases and be adopted company-wide, marketing, supply chain, finance, compliance, and other types of data need to be unified with governance in place. Robust access controls to prevent data misuse are critical when sensitive information, such as the company’s financial performance or customer Personally identifiable information (PII), is ingested.
5. Prioritise areas where advanced analytics can have the greatest impact
By querying and analysing marketing data in one unified platform, companies can increase customer lifetime value, optimise advertising spend, reduce churn. It is important to prioritise outcomes upfront and then communicate those decisions to the entire marketing organisation to ensure that collective energy is channelled in the right direction.