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Data-driven

Bilal Awan - Author
Muhammad Bilal Awan
| October 13

You may have heard the buzzword data-driven marketing. In this blog we will discuss what is required to really be data-driven in marketing initiatives that help us achieve a better return on marketing investment?  

We will talk about:

  • What data-driven marketing is
  • How to create and implement marketing strategies based on data
  • The challenges marketers face in a data-driven environment, and
  • Tools to help deliver a higher return on investment (ROI). 

Today’s marketing is a lot different from decades-old gut-driven marketing. Now we have the most reliable sources of information available in real-time. With tools like HubSpot, Salesforce, Zoho, and many others you can track every interaction of your lead from the initial stages of the buyer’s journey to post-purchase.  

This helps devise long-term strategies that are based on actual data rather than gut feelings. With the information available you can optimize current campaigns to achieve the best ROI. 

However, to achieve the desired results you need to first understand what’s important in terms of your customer interaction and what metrics matter the most, so you don’t get lost in an enormous amount of data. 

Become skilled in data-driven marketing with Data Science Dojo’s certificate programs. 

data driven marketing
Four key benefits of data-driven marketing

What is data-driven marketing and why is it important? 

Data-driven marketing is an approach where marketers build strategies based on the analysis of big data. This includes using tools to drive insights from raw data to turn it into actionable insights based on customer interaction. Marketers identify trends and base their long-term strategy on insights driven by data analysis. 

So, why should we invest in a data-driven marketing approach? Besides the obvious answer of clarity and efficiency of marketing processes, a data-driven approach helps identify a target audience, creates a seamless experience for customers, helps choose the best communication channels, and creates personalization. 

  • Help define the target audience 

One of the most important aspects of any marketing campaign is to have a laser-sharp definition of the target audience. With the help of insights from different marketing touchpoints collected and analyzed, we can define the target group for our products/services who are most likely to benefit. 

Once we have a clear definition of the target audience and created personas everything else falls in place to create a synergized marketing campaign to reach the right audience at the right time with the right communication. 

 

  • Create a seamless customer experience 

Successful marketing is not only about lavish advertising campaigns and promotion but to create and delivering superior value to customers. This in turn helps build the brand, create an army of loyalists, and drive positive word of mouth. 

Data-driven marketing helps analyze trends in the market and understand user interaction with marketing touchpoints to create workflows and processes. This helps improve service delivery and exceed customer expectations. Data-driven organizations are able to deliver a smooth experience over the customer lifecycle minimizing hurdles and delivering great value. 

For example, at Data Science Dojo, customer success is the most important driver of overall organizational health. We have created automated processes that are personalized to each individual customer and lead. This helps the marketing team nurture potential leads into high-value customers and delivers a seamless experience to help build a community of brand advocates. So far, we have trained more than 10,000+ professionals from around the globe and built a community of data enthusiasts. 

 

  • Optimizing communication channels 

With the help of data coming in from different marketing touchpoints, marketers can identify the best possible communication channel for each product category, target audience, and customer segment.  

Marketers no longer need to rely on one size fits all solutions but instead create personalized communication based on user behavior, demographics, psychographics, and other factors being captured through CRM and ERP systems.  

For example, Starbucks, one of the leading coffee brands in the world used a data-driven approach to create an end-to-end marketing experience for their customers by using a mobile application as their primary communication channel. Marketing identified an opportunity to grow the customer base by offering a loyalty reward program based on user interaction with the brand touchpoints. According to Risenews case study today Starbucks is running the most successful loyalty program with over 24 million active users.  

 

  • Creating personalization 

Customers are skeptical about generic marketing messaging that pushes them to buy. A recent study by Marketo shows that consumers are fed up with repeated generic messages being blasted at them. 63% of the respondents said they are highly annoyed while 78% said they will only engage with the brand offers if it relates to their previous interaction. 

Personalization is not just an add-on to good messaging, but it has become a necessity to survive in a cluttered communication environment where users are receiving thousands of brand messages from multiple platforms.  

With data analysis of user queries, interaction, and common questions, and defining the entire sales process marketers can create personalized communication based on user segment and need.  

The sales team plays a vital role in delivering personalized messaging but with a data-driven approach, we can minimize redundant tasks and focus on delivering personalized messaging based on user interaction. 

 

How a data-driven approach helps improve ROI 

Now that we have a clear understanding of how significant data is to any marketing effort, we can talk about its impact on overall business goals and specific measurable marketing objectives. 

Research suggests benefits of a data-driven marketing approach are huge. We get greater customer loyalty, improved lead generation, and increased satisfaction. 

According to ZoomInfo about 78% of organizations that follow data-driven approach verifies increase in lead conversion and customer acquisition. 

Another study by Forbes reveals that 66% of marketing leaders believe that data lead to increased customer acquisition. 

To improve your return on marketing investment it is important to give the right attribution to each marketing activity. This helps us identify the best drivers of growth and invest more time and money in that particular marketing activity or channel. 

Learn more about marketing attribution in this short tutorial 

 

Challenges to a data-driven approach 

According to Campaign Monitor, 81% of marketing professionals consider the implementation of data-driven strategies extremely complicated. 

So, what are some of the challenges to achieving a data-driven marketing overhaul? 

 

1. Gathering data: many data-driven marketers are overwhelmed by the idea of collecting data without any automation. In most cases, the abundance of data makes it difficult to narrow it down to the most useful data for analysis.  

Solution: There are multiple CRM and ERP systems available at very competitive costs that deliver precise information on your customer that can be used to create a better user experience. 

 

2. Pulling data: Manually pulling and updating data regularly is a laborious task  

Solution: Creating a marketing dashboard that helps keep track of real-time data. Less time should be spent collecting data and more time analyzing and making decisions. There are multiple tools available to connect and visualize your data. Platforms like Hotjar, Adverity, and Improvado help collect, organize, and seamlessly visualize data so you as a marketer can focus on planning and making data-driven decisions. 

 

 3. Data silos: Challenge of data silos created at each departmental, functional, or team level which is not accessible to the entire team makes the marketing job difficult. A recent survey shows only 8% of the companies have a centralized data repository.  

Solution: To overcome the challenge of data silos there needs to be an organization-wide effort to modernize and embrace change. This is going to include setting up common standards, changing culture, and embracing new marketing analytics platforms. 

 

A marketing strategy based on data 

Building a data-driven strategy or just strategy itself is a vast topic with much research being conducted on the best way to do so. The only thing you need to keep in mind is your current business environment, this includes internal, external, and current organizational requirements.  

Here is a quick walkthrough of steps involved in a data-driven strategy 

Step 1: Strategy 

The first step is to identify long-term strategy, this means figuring out your long-term goals, specific and measurable objectives, and detailing down to tactics.  

Once you have a clear understanding of your overall business strategy as well as a marketing strategy you can focus on data that is relevant to your goals. 

Step 2: Identify key areas 

Data is scattered across organizations coming from all directions and multiple customer touchpoints. It is important to identify key areas of interest that align with your overall business strategy and objectives. Once we have key focus areas, we can continue investing more in building capabilities in that area. 

Step 3: Data targeting  

After identifying focus areas, it is time to target datasets that will answer all the burning questions related to your business and marketing objectives.  

This means identifying already available information and channels and figuring out the most valuable information. At this point of your data-driven strategy, the goal is to streamline data collection and presentation methods so that marketing can only focus on key areas of business value and not waste time on non-essential data reports.  

Step 4: Collecting and analyzing data 

In this step, you need to identify key stakeholders in data collection and analysis. There may be teams or individuals at each data collection and distribution point based on the size of the organization. The idea is to keep the process of collection and dissemination of data seamless, integrated, and in real-time.  

This may require an organization to implement integrated ERP systems or CRM systems to connect data coming in from various sources based on our identified key focus areas and show relevant information to each team. 

Step 5: Turning insights into action 

The final step of a data-driven strategy is to turn insights gained from data analysis into actionable items. ROI will depend on how useful your insights are and how successfully they were implemented to achieve marketing objectives. At this step, you need to have a clear understanding and a game plan for the implementation phase, actions that will improve business and create value for customers. 

Learn how to visualize data to tell a story 

 

Become a truly data-driven marketer 

Becoming data-driven is a continuous process, if you think you are data-driven now, technology and competitive environment will change in the next 6 months making your current data-driven strategy obsolete. As a marketer you need to constantly improve and update so does your marketing strategy. With this guide, you can get started with becoming more data-driven and less gut-driven to make sound marketing decisions based on real-time data. This will not only help achieve measurable marketing objectives but improve return on marketing investment and improve overall business value. 

 

 

References 

https://www.forbes.com/forbesinsights/data_driven_and_digitally_savvy/ 

https://www.marketo.com/articles/personalization-definition/ 

https://www.campaignmonitor.com/resources/infographics/the-eye-opening-truth-about-data-driven-marketing/ 

https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-big-reset-data-driven-marketing-in-the-next-normal 

https://datasciencedojo.com/blog/data-science-toolkit/ 

 

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