Unlocking New Efficiency: Data Analytics for Sales and Marketing

on April 07, 2020


As Peter Sondergaard rightly says, “Information is the oil of the 21st century, and analytics is the combustion engine”.

A classic example is evident in the marketing and sales process. Data analytics can enhance the marketing and sales processes by providing benefits like strategic decision-making, outcome prediction, customer behaviour analysis, and more. But are you still wondering how effective it will actually be for businesses?

Data science is one of the most in-demand fields in the 21st century, mainly thanks to the vast amount of data available today. The demand for a data scientist is huge, and was ranked as the ’Most Promising Jobs of 2019’. Existing data is a goldmine, which can be used to gain actionable insights and transform business strategies. This has significant impacts on business success in various industries, organizations, and even at the department level

A classic example is evident in the marketing and sales process. Data analytics can enhance the marketing and sales processes by providing benefits like strategic decision-making, outcome prediction, customer behaviour analysis, and more. But are you still wondering how effective it will actually be for businesses?

This article explores how the use of data analytics has long-term value in marketing and sales:


Importance of Data Analytics in Sales & Marketing 


What is Data Analytics Exactly?

The term data analytics covers the various processes to analyze and identify actionable insights and business intelligence from data. This data can be extracted from multiple sources and can vary in terms of size, complexity, or format. Since every business nowadays generates vast amounts of data at high velocity, the need for a specialized data scientist is optimal.

Data analytics may seem easy at the get-go, but in the real world, the analyst has to work with vast quantities of complex data that is continuously evolving and increasing at a breakneck pace. In the data world, this high volume, velocity, veracity, and variety of data makes the process of visualization and analytics extremely complicated. Thus, 69% of businesses believe that data training and empowerment are essential for transformation in the data-driven environment.


Which are some of the tools used for Data Analytics?

This increasing demand for data analytics has led to the emergence of various tools explicitly built for deriving insights from data. Some of the top tools used by data scientists are:


  1. PowerBI: Microsoft’s business analytics solution enables users to generate quick data visualizations by connecting their data outputs to create user-defined reports. The tool is excellent for gaining additional insights and analyzing data holistically.
  2. Google Data Studio: Google’s Dashboard & Data Visualization tool enables users to gain advanced analytics and interactive visualizations from their data, which can be spreadsheets or other forms of raw data.
  3. Qlick: One of the most used business intelligence tools, Qlick, provides an end-to-end platform for data integration, analytics, and user-driven business intelligence. The tool is powerful as it uses sophisticated AI for better decision-making and pattern matching.
  4. SAS: It is a statistical and analytics tool that is used in institutions for data management, advanced analytics, business intelligence, and predictive analytics. The software also has its own language that can read data from common databases and spreadsheets to provide visualizations in the form of tables, graphs, and reports.
  5. Tableau: Recently acquired by Salesforce for US$15.7 billion, Tableau is a powerful and fastest growing data visualization tool used in Business Intelligence. It simplifies raw data into the very easily understandable format. Its visualizations created are in the form of dashboards and worksheets, allowing it to be easily understood by professionals at any level in an organization. It even allows a non-technical user to create a customized dashboard.

How are sales and marketing teams doing with this function?

Many businesses use a combination of reports, research, Customer Relationship Management (CRM) tools, and excel spreadsheets to manage their data. Some of the ways the marketing teams and sales teams generate data and insights are from these are:

  1. Convoluted Excel Reports: Actions, research, and other data points are stored in excel reports, each with its own format, data types, and information. This leads to complexities in gaining insights since the multiple files, data sources, and forms are difficult to comprehend.
  2. Trial & Error Processes: Most revenue-driven processes tend to be a combination of trial and error, as there is not enough data insight that can be derived out of this complex data sources.
  3. Cold Calling To Get Insights: Cold calling has a success rate of 1%-3% to get an initial appointment, and this is ineffective to both the customer and the sales team. However, with the right insights and targeted outreach, the rate jumped to 40% success rate.

data analytics on a board


For smaller organizations, this may seem feasible, but as operations grow larger, and the complexity increases, the ability to generate analytics and manage data becomes difficult. Hence, having a data scientist or analyst in the marketing and sales team is preferred by organizations that wish to have a more data-centric approach.


How is Data Analytics used in Marketing & Sales?


Customer-centricity is the core of every business, and organizations need to align their business goals to the needs of their customers. To achieve this, companies need to truly know the customer, their behaviour, their likes/dislikes, and build trust. In the modern era, “Marketing without data is like driving with your eyes closed.”

Thus, modern enterprises are using a data-driven approach to achieve this, making the use of data analytics for marketing and sales relevant. A survey highlighted that nearly 73% of businesses are making use of data for their organizational growth. Data-Driven Decision-Making enables the companies to capitalize on new business opportunities, generate more revenue, predict market trends, optimize current operational efforts, and fabricate actionable insights.


data graph


Why does Data Analytics for marketing benefit organizations?


  1. Consolidated data: Marketing usually needs to work with data from multiple sources, which could include industry research, CRM, reports, and more. A data analyst for marketing can help to gain actionable insights from various sources and consolidate ideas.
  2. Helps make informed decisions: 65% of marketing executives in a survey have claimed that data-driven marketing is crucial to success. Data Analytics for marketing helps organizations make informed decisions, as data helps to understand what works and what doesn’t. Marketing teams can optimize their channels and focus on the ones that are working while re-accessing the ones that aren’t.
  3. Know your target audience better: Data analytics can help to understand customer behaviour, by providing insights on event tracking, buying patterns, preferences, and more. It helps create campaigns that are targeted towards a particular audience to get more effective results.

How Data Analytics for sales helps make business processes efficient?

Data can be used for targeting ads, but how well does it work for increasing revenue? The key to a successful sale is ensuring the sales team is engaging with the right customer, and providing the personalized solutions that address their business problem and fit into the client’s budget. Without the right data, doing this is a matter of trial and error.

Data Analytics for sales enables the sales team to gain better customer insights by:


  1. Streamlining customer data for better insights: Understand what the client wants by tracking various sales metrics like product performance, regional sales analysis, average purchase value, the average time to close, and more. These metrics and the present information on particular customers can help to create a sales process with higher success rates.
  2. Know what is selling: According to Marketing Metrics, businesses have a higher chance of selling to an existing customer (60%-70% success ratio), while the probability of selling to a new prospect is only 5%-20%. Data analytics can help sell to both target groups, as it provides better insights on each customer to improve the decision making process.
  3. Analyze overall sales process: While improving the success ratio, data analytics for sales also helps to monitor and track the organization’s sales processes. Metrics like sales growth, conversation ratio, sell-through rate, and others help to track sales performance. It also helps to analyze where it needs to focus and what needs to be done to maximize success.

Data is here to help businesses effectively perform their marketing and sales functions. Still, the shift to becoming a truly customer-centric business is complex and requires a long-term focus. To execute and gain insights through data, organizations need well-organized teams of data experts to optimize and acquire the right intelligence from data analytics.


Learn to use data analytics for marketing & sales.

The surprising insights may have many wondering why it is not part of the mainstream process yet. The lack of understanding around data science, the aversion to technology and technical terms, and the displacement of set procedures and infrastructure pose a significant roadblock. Some of the ways to tackle this challenge are:


Create A Data-Driven Culture

It will be astonishing to know that only 0.5% of all the data we have created is ever analyzed and used. This happens mainly due to lack of resources, technology, and the complexities involved in gaining the right insights.

Being data-focused doesn’t happen overnight. However, with a more data-focused culture, organizations take the first step to create a roadmap for being data-driven.


Manage The Talent Gap

Finding the right talent can be a significant gap for companies that wish to be data-focused. Despite the high demand, data science is still relatively unfamiliar. This gap can be bridged by in-house training in data analytics and enabling employees to take up new initiatives focused on ensuring proper usage of data. Making your employees data-savvy is the right way to grow your organization with a long-term focus.


Define The Role Of Data Analyst In Marketing & Sales

Despite having data scientists, many organizations fail to gain actionable inputs as their roles are not clearly defined. To ensure the marketing and sales teams, as well as the data analysts working on these, have a clear goal, identify the purposes for data scientists and analysts within the revenue departments.

Doing so ensures data analytics can help the marketing and sales function be efficient, with minimal disruption of existing processes.


sales analytics


Conclusion

Data science is not just a field for a particular industry or domain; it is vast and can be used with every business, function, or market. As companies are becoming more data-driven, this is the ideal time to hone the skills and be one among the fleet of data scientists and experts.

If you want to build a career in data analytics or want to add new skillsets to serve your organization effectively, why not explore a full-time immersive Data Science & Machine Learning Bootcamp? For more details, check out the link and get in touch with us to know more.