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Let your data guide you in making important marketing decisions.


The marketing industry has transformed over the last few years to become more technology-enabled, where marketers are asked to be also play the roles of Data Analysts, Strategists and Business Development Managers. So how can marketers leverage the data that they already have to enable them to lead the way?


Data Analytics Can Drive Your Marketing Strategy


Before you develop a Marketing Analytics road map, it’s critical to understand the basics. Here are a few necessary components to your plan that you must determine before you set out on your Analytics journey.What data do you need to measure?


What key metrics will you measure for each data set? What cadence will you need to report on your data? Will your Dashboard be static, and exported regularly, or dynamic (updated in real time)? Who is responsible for what?


Understanding these key criteria is the first step in developing a clear reporting strategy. For small marketing teams, it can be helpful to partner with Analytics teams, like NLP Logix, that focus on Data Analytics as their core expertise, 24/7. For larger teams, even if they have Data Scientists in-house, resources can often be stretched thin. Finding bandwidth to develop internal Dashboards and processes can often drop on the priority list. It’s important to identify a partner that can not only perform the essential duties of developing a Marketing Analytics Dashboard, but to uncover a team that can guide you along the way. We like to say, “Data Science is a Team Sport®.” It’s important to combine skill sets from Data Scientists, Statisticians and Mathematicians as well as Marketers and Business Leaders.







Once you have determined the basics of your Data Analytics approach, you start to pull the data into a central source of truth. A Marketing Analytics Dashboard is not only valuable to a company’s marketing department to measure success and optimize campaigns, but can be leveraged to provide transparency to a company’s leadership team and start to influence strategy within the organization.


Through the integration of Data Analytics and the development of a robust Marketing Analytics Dashboard, there are four key areas where you can optimize your marketing strategy.


  1. Persona Development
  2. Targeting Criteria
  3. Determining ROI
  4. Predicting Future Trends


We’ll take a look at each of these areas to unlock how data can help you develop a future-proof marketing strategy. And even more, how a Marketing Analytics Dashboard can help you to visualize this data in a more consumable and influential way.


Develop Personas Based on Real Life Data


One of the biggest challenges of Marketers is how to leverage their own data. Even if your company has a large database of contacts, it can feel impossible to organize these contacts into logical and strategic contact lists. Making sense of your contacts can feel like a daunting task. Rather than scrubbing rows and rows in an Excel Spreadsheet, or going contact by contact in your CRM, a team of Data Scientists can strategically cluster your contacts into unique Personas based on criteria such as demographic data, geographic data, customer behavior, online content consumption and even frequency of date/time interactions and engagement levels.


Marketing Analytics Dashboard


Target Audiences with Similar Criteria


Through the development of a Marketing Analytics Dashboard, you can more strategically target audiences and users, both on and offline. Whether you are analyzing internal data, or integrating third party data from outside sources, a holistic view of your contacts’ unique identifiers should drive your advertising strategy. Whether you are running a Direct Mail campaign, or targeting through social media, understanding the nuances of your data sub sets will increase the success rate of your marketing messages.


Visualize your results to measure ROI


All marketers must report on the success of their campaigns, and optimize along the way. There’s a mountain of data accessible to you – through search engines, and social media and your CRM. But, integrating multiple data sources into one view can be a massive challenge. On top of that, being able to visualize these metrics and results in a way that is easy to digest and understand, and translating those results into company financial gain – can seem impossible to the brightest of marketing teams. Within a robust, multi-channel marketing strategy, it is a challenge to gain visibility into marketing attribution and financial results, or to develop ROI Modeling to predict future success. A unified view of marketing results through a Marketing Analytics Dashboard is a critical way to understand how your campaigns are performing, and report back to key decision makers.


Understand past performance to predict future trends


The ability to predict future campaign success and influence decision makers to allocate marketing budget is every marketer’s dream. A Marketing Analytics Dashboard can provide more than historical or current results and metrics. Through Predictive Modeling, Data Scientists can develop intelligent formulas to predict future campaign success. Want to know how many leads you can expect if you add $1,000 to a campaign channel? This information can dynamically populate in your Marketing Analytics Dashboard. Now, you can illustrate the future ROI for your campaign strategy, and develop tangible business cases for your marketing activities.


At NLP Logix, we deliver Custom Analytics Solutions to our clients across the globe. We specialize in Natural Language Processing, Machine Learning, Predictive Modeling and Data Analytics. Over the past few years, we have seen a huge demand for Marketing Analytics Dashboards. Identifying this need in the market, our team of Data Analysts, Statisticians and Marketing Strategists are delivering custom-developed, fully integrated, predictive Marketing Analytics Dashboards.

Get in touch with a NLP Logix team member today to see how we can help bring your marketing strategy to life through Data Analytics.




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