Implementing Data Marketing strategy

Implementing Effective Data-Driven Marketing Strategies

How to implement effective Data-driven Marketing strategies? The first step is to assess the current state to set a realistic roadmap from current to overall goals for the future (data location, flows, interactions). Most companies have quite a few platforms storing data about their customers and business processes (CRM, MarTech systems, ERP, data warehouse, BI and others).

Audit of existing systems and databases.

The goal is to understand if the existing stack satisfies the company’s needs and if it can be optimized. It starts with a clearly defined list of business needs and objectives (strategy, marketing, sales, customer experience and customer service, among others).

Next, an assessment needs to be done to understand what problem is solved by each tool and verify if the company really needs it. A full mapping of data flows between all the different systems (sources, direction, types of data synchronized) will help identify a need or room for optimization.

Usually, the sales and marketing team are provided with a vast stack of tools that allows them to connect effectively with current and potential customers. Marketers require the tools and data to create compelling omnichannel marketing campaigns to boost the acquisition pipeline, while the sales teams should have access to a steady flow of meaningful and timely data to engage with new or existing businesses collect custom intelligence data, perform in-depth analysis and turn data into action to improve your marketing campaign, product/service, customer experience or any other area that you can leverage on to get new customers.

Data Quality & Quantity optimization.

How to implement effective Data-driven Marketing strategies? The second step is to ensure data quality across the entire organization.

Data quality is critical when it comes to generating new opportunities and improving marketing efficiency. Accurate and complete data is key for increased engagement and conversion rates, especially to segment the customer and prospect base and personalize communications.

Improving data quality can drastically improve the overall marketing and sales performance of a company. Working with messy data will lead to wrong conclusions and decisions. Indeed, according to a recent Forrester study, 90% of marketers indicate that their marketing campaigns have been negatively affected by low-quality and inaccurate data resulting in financial and business losses.

The consequences should not be taken lightly:

  • Wasted marketing budget, decreased revenue and conversions rates
  • Increased customer churn, reduced customer satisfaction and damaged brand reputation
  • Loss of confidence from employer and colleagues

While problems caused by data quality are easy to explain, those coming from data quantity are still relatively new and require particular attention. The overwhelming volume of data made available to marketing teams has led to a decrease in data quality and processing capabilities.

Among the most common issues we can note:

  • Collecting the right data for a given business need
  • Compiling and reconciling collected data
  • Analyzing data and finding meaningful insights
  • Turning data insights into action

Bad data is always costly, but without proper measures, a business may not only lose potential revenue but face issues with privacy regulations (GDPR, CCPA, CASL, and many others). Identifying the exact nature of the problem is essential to implement corrective measures to ensure data accuracy, completeness, and compliance.

Data Process Optimization

How to implement effective Data-driven Marketing strategies? The third step is to ensure data process optimization across the entire organization and existing technology stack.

The optimization of processes to capture, transform, store, and explore data should be implemented to ensure the continuity of the data-driven initiatives.

These can include:

  • Cleansing of both existing and incoming data flows
  • Internal training to empower business user to become more data literate
  • Optimize systems in place to avoid data silos

Improving data quality and management within a company can have a significant impact on revenue. Marketing teams leveraging accurate and actionable data can double their ROI and conversion rates compared with campaigns that run with messy data.

A data-first approach offers an excellent opportunity for marketers to use the available technology to earn customers’ trust, build authentic relationships, and drive sustainable revenue for the company.

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