Enhancing Marketing and Sales with Data Analytics

Enhancing Marketing and Sales with Data Analytics

With COVID-19 impacting virtually all forms of business, the need to stay connected through digital means has become more important than ever. As we continue adjusting to our newfound work-from-home environments, most companies’ marketing and sales operations have turned fully digital. This is why data analytics—the use of data to understand various components of a business’s effectiveness—has proven itself to be one of the most essential tools to combat the pandemic from a business perspective. When implemented wisely, well-designed analytics programs can deliver significant top-line and margin growth by guiding business teams to make better decisions.

In this article we will explore the many benefits of applying data analytics to two of the most essential business functions: marketing and sales.

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Data Analytics and Marketing

Data-backed customer insights can be used to enhance marketing efforts at every stage of the funnel. Within the big data realm, predictive analytics is one of the most powerful tools for marketing success. This branch of advanced analytics gathers huge amounts of big data to predict future results, which is extremely useful for companies especially during the trying times of COVID-19, where the future often seems to be up in the air. Predictive marketing analytics integrates and utilizes important features such as data mining, statistics, modeling, machine learning and artificial intelligence, all to help provide your company with a bigger picture in order to create a more informed vision for the future.

Below are some of the most useful ways of using predictive marketing analytics

Targeted Content Distribution

Predictive analytics can help you better understand which types of content work better for certain customer demographics, what channels are best to reach them on, and how to customize content creation and distribution.

Customer Lifetime Value (CLV) Prediction

Customer Lifetime Value (CLV) is a prediction of the net profit attributed to the entire future relationship with a customer. With predictive analytics, you can take historical data and use it to forecast the future lifespan of your relationship with each customer and also gain insight on how much revenue that relationship will bring in. This can help you set budgets for customer acquisition and give you more accurate calculations of ROI.

Customer Needs and Product Fit

With useful data on historical purchases, customer behavior, and leads, your business can better understand each customer’s needs and wants. This can lead to valuable insight on how to further develop future products, or make improvements on existing products that aren’t doing as well as expected.

Data Analytics and Sales

In the world of sales, analytics plays an important role in lead generation, automating pre-sales processes, and identifying patterns in customer behavior. Marketing and sales often go hand in hand, but both areas serve a unique function within the business. While marketing is the process of attracting customers and promoting a product or service, sales is the quantifiable outcome from marketing that all businesses expect to see. Otherwise, all the money spent on marketing efforts end up going to waste. Although marketing and sales tend to overlap quite often—especially in the digital age—there are still many advanced analytics programs that are specifically designed for the success of your business’s sales team.

Advanced Lead Scoring

Lead scoring is used to rank leads based on where they are in the sales funnel, thus determining their sales readiness. By using big data, every lead will be ranked and prioritized automatically, which helps inform you on the next step to take with each unique prospective lead.

Lead Nurturing and Segmentation

Lead nurturing is an important process of building relationships with prospects throughout the sales funnel. One of the ways to enhance these relationships is through lead segmentation, which breaks your collection of leads into smaller lists based on their actions, that you can then use for tailored lead nurturing campaigns that send more convincing marketing messages. Advanced analytics can radically improve lead nurturing efforts by using demographic and behavioral data.

Churn Rate Prediction

Churn rate is most commonly used to measure the percentage of subscribers or users who cancel their subscriptions within a certain period. In order to expand, your business’s growth rate must exceed its churn rate. Using predictive analytics can help you identify the warning signs of a customer losing interest, which gives you time to conduct the necessary follow-up initiatives or lead nurturing before the customer decides to leave.

Here at Apping Technology, we customize and deliver technical system solutions that help your business grow, including marketing and sales management information systems and other software designs that integrate seamlessly with your pre-existing CRM/ERP systems.

Written by
Andrew McNaughton
Client Engagement Specialist | Apping Technology

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