Marketing Data: Everything You Need To Know

Conduct Research

Examine possible B2B data suppliers' track records for dependability, customer satisfaction, and cost-effectiveness. You should also inquire about their data quality, accuracy, and depth. Read reviews and testimonials from prior customers as well.

Consider Your Needs

Before assessing any providers, consider the type of B2B data you require. Consider the segmentation criteria you require (for example, company size and industrial sector), as well as the manner in which you want your data delivered (e.g., CSV file).

Compare Providers

After you've discovered all applicable supplier candidates, compare them to see which one best matches your needs. Check if the source can consistently give correct data at an appropriate pricing point for your business budget.

Ask For Their Validity

This is perhaps the most important when buying a b2b email database. Ask the providers on your radar whether they are compliant with modern data privacy rules ( such as GDPR, CCPA, CASS, CAN-SPAM, etc.). Also, whether the telephone numbers are DNC compliant and postal addresses are NCOA- verified. If a company complies with all these regulations, perhaps the company is legit, and you may focus on the other points.

Test Out Providers

It is often vital to test out various services with a few vendors before making a final decision to ensure that you are selecting the proper B2B data supplier for your business needs. Before committing to anything long-term or costly, you might want to ask for sample datasets to evaluate overall quality and accuracy levels for each provider's products. A lot of the top data providers offer free email list samples to try.

Better Serve Customers

Organizations can use email list data to identify what consumers like. For example, it can help firms determine the most cost-effective method to address customer inquiries and issues, reducing problem resolution times and improving customer experiences.

Identify New Business Opportunities

Mailing lists provide information that assists organizations in establishing new revenue streams by inventing and developing products and services that satisfy consumer wants. For instance, A retailer of women's shoes can notice trends that indicate a popular style or brand of shoes. They can then respond quickly by tailoring their products and services accordingly.

First-Mover Advantage

Mailing lists provide information on industry trends, allowing firms to respond to market developments more quickly. This can help firms predict future trends, recognize consumer patterns, and spot new business prospects more quickly, giving them a competitive advantage.

Improve Sales

Every business wishes to improve revenue growth. In today's competitive global marketplace, data plays a crucial role in identifying and translating data into revenue opportunities. By leveraging a mailing list, a leader can identify problems and develop sales and marketing strategies that can improve performance and grow revenues.

1. Segmentation

This is an important phase in email marketing and other forms of brand communication. Make sure to segment your customers so that you can offer them the right content and include them in the right campaigns. This simple strategy will significantly increase conversion rates. Segment your data by Job title, business, geography, industry, product interest, and other factors. The more you segment, the more targeted your messaging will be. As a result, your engagement will be higher.

2. Personalized Experiences

Personalization is always effective, especially in marketing. The ideal method to personalize content is to customize their feeds and interactions based on their demographics, online habits, purchase history, browsing history, and other important information.

Let's take the example of Amazon to give you a feel of how effective personalized experiences are. Amazon is a unique example of a company using personalization to enhance the customer experience. The online retailer uses data such as purchase history, wishlists, and browsing behavior to suggest personalized product recommendations to each individual customer. This personalized approach has been a key factor in Amazon's success and has helped establish strong customer loyalty.

3. Customer Journey Mapping

Marketing data plays a crucial role in defining customer journey mapping. This is because it provides insights into customer behavior, preferences, and pain points that can be used to map out their journey from awareness to purchase and beyond. This data can be used to identify key touchpoints in the customer journey and tailor marketing efforts to each stage.

4. Data-Driven Decisions

Data-driven decisions refer to the process of making strategic choices based on data and data analysis. The purpose of using data to inform decisions is to improve the accuracy and efficiency of the decision-making process and to make decisions that are more likely to result in positive outcomes. In order to make data-driven decisions, organizations must first gather and analyze data and then use the insights they gain from the data to inform their decisions. This often involves the use of data analytics tools and tactics such as data visualization, statistical analysis, and machine learning. The goal is to use data to better understand the market, customers, competitors, and other factors that impact the success of a business and then use that understanding to make informed decisions that drive growth and improve performance.

5. Omnichannel Marketing

Omni-channel marketing is a comprehensive and integrated marketing approach that reaches customers across multiple channels, such as email, social media, mobile, and in-person interactions. This approach creates a seamless and consistent customer experience, regardless of the channel they use to interact with the brand. As consumers gain more power, omnichannel techniques are becoming more common across industries; nevertheless, they are especially prevalent in retail, healthcare, finance, and automotive.

1. Data Quality

One typical issue with marketing data is that you can never completely trust it. According to a Forrester report, while 78% of marketers believe a data-driven marketing strategy is critical, up to 70% admit to having low-quality and inconsistent data.

According to another study conducted by KPMG and Forrester Consulting, 38% of marketers have a high level of confidence in the data and analytics that drive their consumer insights. However, only one-third of them appear to trust the analytics generated by their business operations. This problem could be caused by a lack of data collection and analysis. In reality, transparency and data ownership are critical components of any marketing concept or approach.

Solution

Marketers must maintain a data-driven approach for their teams. It's critical to have the right tools, people, and procedures in place to keep your customers' data trustworthy throughout time. Verify and validate your data once a month, or hire a data provider to append and cleanse your list if you don't have the time or resources.

2. Data Overload

As a marketer, you may believe that "the more data we collect, the more we understand audience behavior." However, the irony of having too much data is that you often have little information. This is due to the extensive amount of varied information you have, meaning the more data and fields collected, the less they overlap. As a result, "holes" will appear in the data.

It will be challenging to convert all of the available data into useful insights and fuel business results. It means you'll almost certainly come to no conclusions about your target viewers' purchasing habits. That is why, according to 53% of marketers, "you can never have data explosion on your marketing analytics management."

Solution

Rather than acquiring data and then deciding what to do with it, it is always better to grasp the aim of that data gathering. What do you want to do with the data? And what do you want to gain from it? This allows you to get more focused and informative data from your audiences. And always ‘segment’ your data.

3. Data Privacy

Did you know that 41% of marketers believe that their biggest challenge will be tracking the appropriate data? This is no surprise considering that Data privacy is a major challenge in marketing data as it involves handling sensitive information of customers, such as their personal details, purchase history, and online activities. When it comes to pushing your organization toward expansion and innovation, data privacy should be at the top of your priority list. An essential component of both of these is ensuring that third parties cannot access, utilize, or disclose your private user data, which can protect your employees, secure your business processes, and protect your company's brand.

More often than not, this challenge appears because of the lack of appropriate security measures and adequate countermeasures.

Solution

Data privacy issues can have far-reaching consequences, jeopardizing a company's personal information, financial affairs, and consumer privacy. As a result, it is crucial to take some countermeasures and implement some effective techniques such as developing adequate SOPs, monitoring data trade, avoiding data hoarding, and strengthening data protection plans.

4. Data Silos

Data Silos are one of the most persistent and aggravating problems that marketers face. When data is siloed, it obscures your view for critical insights, making it difficult to optimize your marketing campaigns. The problem usually arises when different teams in your firm use incompatible technologies that prevent them from sharing data.

Data silos make it difficult for marketers to measure marketing performance comprehensively.

Solution

Marketers may eliminate data silos by implementing a single data integration platform across all departments.

Case Study 1: Nike's Data-Driven Marketing Strategy

Nike is an International corporation that is engaged in the design, development, manufacturing, and worldwide marketing of footwear, apparel, equipment, accessories, and services. Nike, being one of the world's largest sports brands, was not lacking in exposure or attention. However, the company noticed that its typical, big-budget advertising strategy was yielding fewer results over time. People aged 15 to 45 make up the largest market for Nike products, spending 20% more than any other age group. These Generation Y clients, on the other hand, were not interested in huge, top-down media and were searching for a brand that delivered constant change and innovation rather than the same old thing over and over. Nike recognized that a new approach was required to reach this demanding audience.

After realizing that marketing in the digital world is all about data, Nike reduced its spending on television and print advertising by 40% between 2010 and 2012 but boosted its overall marketing budget to $2.4 billion in 2012.

Nike sought to address this new, technologically sophisticated audience with a combination of technological advances, marketing data, and social media involvement. Engineers and scientists from famous institutions such as MIT and Apple were employed to create intriguing new technologies and investigate market insights. One of their most notable triumphs was the introduction of Nike+ in 2010 - a device that allows users to log their workout routines, upload them to the web, measure their progress, and share their victories socially. The Nike FuelBand was also added to the product line. This new community generated massive amounts of data, which Nike utilized to track customer behaviors, construct online communities and places for Nike fans, and form meaningful interactions between the brand and its customers. Nike brought its social media marketing staff in-house to better understand the data and interactions created by its supporters.

was the result? Nike's innovative technique of using data to get user insight and developing a diversified, sociable, and engaged digital strategy was a huge success. Nike reached nearly 200 million people every day as a result of this. Massive amounts of freely shared user data generated important brand insights that contributed to product breakthroughs and helped the brand to become more personal with its customers.

Furthermore, this data-driven approach provided some additional benefits, such as:

• Nike's share prices increased by 120% between 2010 and 2012, which is essential given that every corporation seeks to produce money.
• Nike+ membership increased by 55% in 2012, with 7 million users signing up for the service, the majority of whom connect with the brand many times per week to upload and check their workout statistics.

Case Study 2: Netflix’s Retention Rate Increased to 93%

Netflix is unquestionably the most popular online streaming platform for movies and TV shows, and it owes its success to Marketing Data. It allowed data-driven insight to help them to make logical decisions with a high possibility of success through the clever use of data (through business intelligence). Netflix used the power of its data smartly to do predictive research to determine exactly what its viewers would be responsive to and interested in watching. They were able to make profitable bets on producing widely-acclaimed shows such as 'House of Cards' and 'Arrested Development' by evaluating over 30 million 'plays' every day, as well as over 4 million subscriber ratings and 3 million searches. This helped them reach the best retention rate in the market within the industry, which is 93%, a significant amount compared to their primary competitors. They are also fast expanding as a result of their original movies and TV shows, which demonstrate that they truly listen to their customers.

How else do they use their data? They collect information such as the time spent watching the show by their subscribers, whether they binge-watched it or took their time finishing it, and whether they paused the show and resumed it after pausing.

This helped them create personalized accounts for each consumer!

Their ultimate goal is personalization, which is evident in their future plans, which include employing AI to design trailers - since why should everyone get the same one? They intend to create trailers that are completely tailored for their viewers; for example, if a given user enjoys romance films, they are more likely to see a non-romance film if the teaser contains romantic elements. That is only the beginning.

Netflix processes all of this information through a complicated algorithm that tailors viewing recommendations to each individual client. This is critical to Netflix's business because 80% of video streamed comes from one of their recommendations. Netflix has essentially used their data to ensure they have 'recurring consumers.'

What is the bottom line? Netflix is, first and foremost, a business, and its use of data must help them generate a profit. To say they are successful is an understatement. Netflix's algorithms save them a stunning "$1 billion per year in subscriber retention value." Their data also enables them to charge the value that provides the best value to their viewers at a cost that benefits both the customer and the firm. This revenue is reinvested in the content (and data algorithms) that have propelled Netflix to the top of the streaming entertainment market.