What is Data-Driven Marketing? And How to Use it.

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Thanks to social media channels and the widespread utilization of different devices, we currently live in a data-rich environment. Companies have taken advantage of big data to gather the information that users leave online in order to target and inform their marketing communication.

Many companies have recognized the importance of data-driven marketing. A recent report on Data-Driven and Customer-Centric Marketing by Forbes Insights revealed 64% of companies take data-driven marketing seriously.

Another study by IBM shows that companies with a detailed understanding of customers perform 60 percent better than the competition. Hence, it does not come as a surprise that 78 percent of marketers currently use data systematically while enterprises that use insights gained out of data-based marketing have even more than doubled since 2013.

Data-driven marketing involves the use of information in initiating marketing actions. This information is then better adapted to ensure it meets the needs and desires of customers. The main aim is to understand customer behaviors better and base marketing strategies on such understanding. And to attain this, data is gathered purposefully at all touchpoints that a customer encounters in their journey, for example, online stores, social media, and corporate websites. It helps in formulating and optimizing marketing actions. However, the challenge is combining various customer information streams collected both on- and offline.

There are many purposes that data analysis may fulfill in marketing including:

  • Measuring precisely and improving results of campaigns in online marketing.
  • Campaign personalization leading to performance improvement.
  • Optimization of communications on social media.
  • Helping in developing content relevant to users
  • Achieving content marketing that employs targeted topic planning.
  • Improvement of customer service.
  • Increasing customer satisfaction.
  • Strengthening loyalty of customers
  • Predictive analytics or prediction of certain events
  • Helping in making timely and accurate decisions.

Tools for gaining data-driven marketing insights

Data-driven marketing is a complex exercise owing to the variety of data supposed to be linked. For this reason, specific analysis and reporting tools can assist companies to collect, structure, and even evaluate data. There is a need to monitor the right KPIs in the respective channels.    

  1. Web analytics tools

The most common web analytics tool is Google Analytics. Through the integration of Google Analytics, it’s possible to analyze user behaviors. It includes recording certain KPIs like the number of page views, website traffic, and the length of stay. Some of the available alternatives to Google Analytics include Piwik, E-Tracker, and Chart Beat. 

  • Tools for social media analysis

Social media monitoring and social listening tools help in measuring relevant KPIs including mentions, interactions, and shares, and analyzing the tone of reports on brand and identity trends. It then contributes to the optimization of communications through social media. Examples of social media analysis tools include Sysomos, Brandwatch, and Vico.

  • Marketing automation tools

These are software programs combining web analytics across various channels of communication. Tools such as Hubspot, Marketo, and Silverpop can be used for planning, setting up, and analyzing personalized marketing campaigns. The operations collect data on users who, for instance, visit particular online stores or landing pages. These expressions of interest are useful in formulating appropriate and targeted campaigns in line with the behaviors. Moreover, marketing automation tools help with lead management and are integrated with other social media channels such as Twitter and Facebook.

  • Customer relationship management systems (CRM)

Data that marketing automation tools generate is linked to the CRM system. CRM refers to software programs essential in the management of customer relationships through the collection and storage of all customer data-from addresses to purchases. This data is stored in a central customer database. Salesforce and Sugar are examples of CRM systems that help in managing interactions with customers and deploying targeted customer care. These systems are used more by marketing, sales, and customer care departments.

Through these tools and technologies, data is collected to inform online and content marketing and to effectively manage communications in the digital world. Data provides a more clear understanding of the customer journey and develops content tailored to suit customer needs. Data-driven marketing assists interact with prospective customers, matched to an appropriate phase of the customer journey. Also, data facilitates KPIs optimization along a customer journey. Rubedo can be very helpful for this.

Data Analytics Techniques

Some examples of marketing analytics techniques are:

  • Web analytics: measures views, device traffic, and any other activities.
  • Metrics for content offer or “lead magnet”: These are just simple measurements like call-to-action (CTA), click-through rates, and other complex data, for example, the generated leads ratio to marketing-qualified leads (MQL).  
  • Email marketing metrics: Including open and unsubscribe rate.
  • Social media and content metrics: follows, engagement rate, and shares.
  • E-commerce metrics: including shopping cart abandonment rate. 

Advanced marketing analytics uses complex models to provide intelligence such as:

  1. Customer lifetime value
  2. Marketing attribution: evaluates the effectiveness of campaigns and attributes success or failure to various channels and presentations.
  3. Clustering: groups customers on basis of personal characteristics.
  4. Conversion prediction: list users would most probably become customers.
  5. Forecasting
  6. Anomaly detection

Examples of Data-Driven Marketing

E-commerce retailers extensively use data-driven marketing in supporting customer experience while increasing sales. An example indicated in Harvard Business Review is the Vineyard Vines, which is a fashion brand with brick-and-mortar stores and an online product catalog. This company uses artificial intelligence (AI) platform which helps gain some insights about customers from the actions on the e-commerce site, taken or not taken. Social media or email communications are triggered automatically at particular points including cart abandonment. Insights further refine search engine marketing.

For business-to-business marketing where certain inbound leads should be captured and nurtured, tactics are aimed at long-term retention of the prospects rather than urging them to purchase. Content marketing is used frequently and prospects could be offered white paper or some other high-value information resources in place of an email address. Hence, marketing automation tools always support continuing activity through the customer journey.

Conclusion

Data is used by marketers as a crucial decision-making tool and is always essential in analyzing and enhancing marketing performance. 

Moreover, strategic data use contributes to higher turnover, with recent studies indicating nearly 57 percent of companies report data-driven marketing producing a substantial increase in the ROI of their campaigns.

However, the development of data-driven marketing could be a major challenge. Companies should have the right tools and staff to correctly interpret, manage and integrate data.

Usage of data helps companies act flexibly and consistently optimize content and online marketing campaigns. Thus, marketers have to routinely use data in aligning their products and offers to prospective customer needs.