Using a data platform to power personalised marketing campaigns

Every day businesses gain more data about their interactions with customers, yet many continue to struggle to make use of it for personalisation and analytics.

Data may be stored in multiple locations and in different formats, making it difficult to combine to achieve a single view of each customer. As a result, customer experiences suffer and relationships erode.

To overcome these challenges, increasing numbers of organisations are deploying data platforms that allow easy customer data consolidation and analysis. These platforms ingest first-party customer data from multiple sources in real time, and then consolidate profiles on an individual basis. First-party data can also be combined with third-party data from a data marketplace to provide deeper insights.

The platform then enables marketing teams to segment and share these profiles thereby allowing personalisation of email campaigns, digital advertisements, and other communication activities. 

Key steps in a data platform strategy

When deploying a new data platform to gain better value from your customer data, there are five key steps that should be followed. These steps are:

  1. Map out a comprehensive data strategy:
    To avoid taking an ad-hoc approach to data management, begin by creating a comprehensive strategy that covers all data generated and held by your organisation. This avoids a situation where different teams take different approaches and there ends up being multiple, disconnected storage silos.

    Firstly, the strategy needs to address the human resources that will be required. It’s likely you will 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. 

    The strategy should also identify exactly who needs access to data, what are they trying to achieve, and how will the value they create be measured. Once this has been confirmed, the strategy should identify the technologies that will be required. 

  2. Identify all data sources:
    By carefully identifying the marketing data sources required to meet strategic objectives, an organisation can avoid the complexity and expense they might incur by grappling with more data than they actually require.

    Some customer data, such as purchase history, is stored in internal databases, but most data will need to be ingested from its original source. To avoid burdening engineers with ongoing data maintenance, marketing organisations should make use of ETL tools with prebuilt connectors to data sources. These tools can then extract data from the original source, clean it or change it into a useful form, and load it into the company’s data warehouse. 

  3. Create a single source of the truth:
    Once all the marketing data has been located, it needs to be stored in a single platform that supports both semi-structured and structured data. This infrastructure needs to be sufficiently flexible and scalable to enable near real-time data integration. It also needs to be able to provide a single source of truth that a variety of teams can use.

    The platform should also be able to be readily scaled to meet increasing demand over time. Such instant elasticity removes scheduling and data batching concerns, letting data scientists run complex models and enabling nontechnical users to access dashboards whenever they need. 

  4. Ensure data is available to non-technical users:
    To unleash the maximum value for your organisation, it’s important to think beyond the productivity of data scientists. The platform should also be readily accessible to a large number of less-technical users across business functions, including operations, compliance, business development and marketing.

    It should also be remembered that robust access controls will also be needed to prevent data misuse. This is particularly important when the data being used is sensitive or personal in nature.

  5. Focus on making use of analytics:
    By being able to query and analyse data in one unified platform, organisations can increase customer lifetime value, optimise advertising spends, and reduce churn. It’s therefore very important to prioritise outcomes up front and then communicate those decisions to the entire marketing organisation to ensure everyone understands the overriding objectives.

By taking a platform approach to the storage and analysis of customer data, organisations will be in a much better position to personalise effective communications and marketing campaigns. Those that manage to reach this position will be rewarded with strong and more valuable customer relationships in the years ahead.

By Peter O’Connor
Vice President Asia Pacific and Japan


Written by Guest

This article was prepared by a guest blogger and/or reprinted with permission and thus the opinions expressed may not necessarily reflect the opinions of Fifth Quadrant.

Topics: personalisation digital marketing CX Articles & Insights big data marketing automation

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