How to Use Data to Make Better Marketing Decisions

In the digital age, the race among businesses to increase their market share has grown significantly. Companies use various branding and marketing methods. This race is likely to intensify as many businesses have shifted to online sales. The most common type of marketing strategy is data-driven marketing. Under this approach, companies try to uncover consumers' real needs through surveys and other tactics. For example, during the pandemic, demand for medical supplies surged. Businesses already selling medical products saw huge profits. But other companies, by studying market trends, seized the opportunity to enter this market and earned substantial profits. That's how data helped companies make money. But this is just one small example of leveraging data for advantage. From another perspective, large organizations collect data about their customers or website visitors by observing behavior on their sites. They are most interested in which products are purchased most often and how willing consumers are to buy your product. This enables them to better understand shifting consumer trends and adapt to the ever-changing market. Looking further, this data can be used in big data analytics to process information in real time. This information helps companies decide how to respond to changes in market trends.

What Is Data-Driven Marketing?

To increase your market share, you need to choose effective methods in all aspects. I mean ensuring that your customers get what they want to see in every way. However, this doesn't mean changing your usual approach or adapting unnecessarily. Broader thinking will help refine your methods, and that's how businesses evolve. Websites typically target potential buyers and shape their results according to customer needs. They use various methods to attract customers. If you optimize your site to be more customer-centric and focused on specific buyers by answering common questions, that's called data-driven marketing. It helps direct buyers to your brand or site. For example, if someone runs a clothing brand and their annual revenue doesn't meet standards, they'll choose methods based on buyer preferences. They will identify demand among different groups and adjust their products. To illustrate, let's look at variation in people's choices.

Some cannot afford expensive dresses and look for items within their budget, while others prefer more modern styles and choose costly items. The owner will need to gather this data and present products accordingly. Other methods include running various ad campaigns, effective promotion strategies, and creating targeted automated emails. Research has shown that analyzing information is the best tactic for business growth, and that's correct given that nowadays people buy what they like. Moreover, they follow trends.

Furthermore, quantitative and qualitative analysis are two different tactics that should work simultaneously like global trends. Quantitative analysis uses data based on multiple demands for a specific product and is a statistical approach. Qualitative research, on the other hand, relies on observation and covers the creative side of business.

The importance of data-driven marketing lies in rapid business growth and satisfied customers. It helps you gather relative information that centralizes customer requests.

Benefits of Using Big Data in Marketing

Big data is vital for your business in an era where characteristics change in an instant. You've likely heard the clichéd story of the tortoise and the hare when they decided to race to determine their speed. The hare considered himself faster than the tortoise and slept on the way, while the tortoise was wise. He slowly reached the destination before the hare. Similarly, if you think your business is the most successful, you'll be like the hare. So companies need to use big data. But why should you do it? Big data offers many benefits.

HELPS WITH PRICING:

For example, it allows you to set prices based on customer class and loyalty. Setting prices without considering the context will waste your efforts. Adjustments in pricing directly affect buyer ratios. Using the right information from big data at the right time is essential. If you offer a lower price, people will be more attracted to your brand, and ultimately your revenue will increase. Planning is crucial at every stage of life, and big data enables better planning. It provides the necessary

information about volatile market trends. It has been proven that companies that modify their products accordingly have an advantage over others.

BETTER CUSTOMIZATION:

Everyone has their own tastes and styles. Big data allows you to present people's choices in a systematic, easy-to-analyze format. With big data, brands can tailor their products. This helps meet the needs of different sectors, thereby increasing customer satisfaction.

BETTER FORECASTING:

Big data helps predict future sales outcomes and other customer responses. This is based on thorough analysis of past statistics and determining future successes or losses.

MEASURING ROI:

Measuring ROI can sometimes be difficult even for professionals. Big data eliminates the error of incorrect marketing tactics and budget allocation.

ENHANCING ADVERTISING EFFECTIVENESS:

Advertising plays a leading role in business. It convinces customers and promotes your brand. In the past, advertising was generic, but with technological advances, it has become personalized. This helps deliver more engaging content to people. With big data, you can personalize ads and persuade a larger audience.

Common Challenges of Data-Driven Marketing:

LARGE DATA COLLECTIONS:

Compiling big data can be chaotic, as it often collects tons of information, making it difficult to find what you need. Sometimes it includes useless details about every incident. Therefore, creating a system that properly organizes this information is important. When collecting large volumes of information, sorting becomes an issue. For example, when gathering massive data, risk managers often overlook necessary data and pick simpler ones. This can lead to ignoring real-time data and negatively impacts decision-making. It's crucial to have a more advanced organizational system that can automatically notify you of changing trends.

GRAPHICAL REPRESENTATIONS:

Receiving information about changes in features in real time significantly increases the chances of making better decisions. To accurately understand trends, it's essential to have graphical or pictorial representations of data. However, this task is time-consuming. Data is collected from various resources and stored in different systems. Employees' lack of awareness about this can lead to inaccurate analysis. A centralized system will gather information regardless of location and allow for more accurate comparison. The downside of a centralized system is that it may not be accessible to everyone. Risk managers need access to every piece of information for detailed analytics. This enables them to make decisions quickly. Data entry can increase the risk of errors and affect the decision-making process.

Reducing Human Error:

Data entry using software reduces the risk of human errors. No one can work under pressure, and risk managers take a lot of time to collect data. Therefore, a calm environment must be ensured. It is vital to provide risk managers with proper support, as without it they cannot work effectively. They should have access to all the data needed for analysis. Risk managers sometimes feel uncomfortable transitioning from traditional data analysis methods. Therefore, they should inform their employees about the latest technologies and provide detailed tutorials. Another issue for risk managers is that they are not allowed to spend beyond a set limit. Using new technologies requires skills. Employees' lack of skills can hinder deep analysis.

Examples of Data-Driven Marketing Strategies:

About 29% of marketers find data analysis more useful in marketing. Data-driven marketing has a lot to offer marketers. You can use data in various forms and process it to make it useful for marketing purposes. With it, you can shape different strategies that help improve the quality and effectiveness of your overall marketing. For example, when a user buys something on your site, they may be asked a series of questions.

This could include various analysis-related queries, asking what prompted them to try a particular product, how they found your site, or even what made them choose you over competitors. This way, you can learn more about how customers come to you, allowing you to focus on that marketing channel. You can even ask customers for feedback after a sale, which helps eliminate product flaws and improve user experience, boosting sales.

A data-driven chatbot is very useful because not every visitor is equally important to your business. Suppose a visitor starts interacting with a chatbot. This usually means they are interested in your product and want to learn more. This data can be used to

make your product more tailored and user-friendly. If you have reliable data about a specific product or service, creating content about it is appropriate. Most trendy items have high search volumes, and if you have ready content on that topic, you'll likely see an increase in viewers. More viewers likely lead to higher conversion rates. Thus, you can increase sales through reliable data.

70% of marketers consider SEO a more beneficial marketing tool than PPC, so you can also use SEO to increase viewership. You can use search engine optimization to improve your site's ranking in search engines. As a result, buyers trust you more because you have a stronger online presence.

Secondly, you'll also see significant positive changes in potential buyers' perception of your site. This leads to higher conversion rates due to a positive brand image and good optimization of your site and content.

Thus, with the right approach, data-driven marketing can generate a large number of leads for your business. It's important to note that the data must be reliable; otherwise, you'll encounter problems.

How to Create a Data-Driven Marketing Strategy?

To create a strategy, you need to consider several factors when deciding how to use data to implement a well-thought-out marketing plan.

INFORMATION ON AUDIENCE PREFERENCES:

First, you need to know your target audience and the segment you intend to target.

You should gain insights about your consumers: think about who will buy this product and their budget.

Align your product with their budget and analyze whether it can meet customer needs.

If your product meets all requirements, congratulations, you've hit the right segment. You're on the right track to move to the next step.

THROUGH THEIR AGE AND INTERESTS:

The next step is to find the best ways to market your product.

Different products require different types of advertising. Not every product suits the same advertising method. For instance, Facebook ads work best for people aged 25-35, while Instagram ads are good for teenagers because most are young. Now you need to figure out the average age of your product's users.

Suppose you sell video games. They are most popular in the 14-25 age range. In that case, email marketing or website ads won't help.

To capture gamers' attention, you need to use appropriate platforms.

In this case, TikTok, Instagram, and Snapchat are better because their average user age is lower.

Thus, you can reach the maximum audience and avoid wasting effort on the wrong platform. However, it's best to be careful when choosing an ad platform.

With proper research, you can select the right platform. After finishing research, move to the last step.

THROUGH DETERMINING CUSTOMER LOCATION:

The final step is to identify the target location. Location matters because each region has different requirements for various products.

Using the video game example again, the best market for selling them is in more developed economies.

Because these countries have higher GDP growth and more disposable income for luxury items, they can spend money on video games, which are luxuries.

Compared to Asia, which is not too into video games, and most low-GDP countries, Europe and the US are the most suitable places to market video games.

Why Your Marketing Should Be Data-Driven:

BETTER PLANNING:

Data-driven marketing offers a host of benefits. It requires investment to extract data, but why should you invest? Data-driven marketing not only increases satisfied customers but also highlights the need to make changes to improve your business quality. And who doesn't want their business to climb the ladder of success? When you meet people's demands, it ultimately increases your revenue. Plus, it allows you to plan future strategies and develop more effective tactics. Competition exists everywhere. Competent people surround the market. It's best if you are ready to beat the competition. Using data-driven marketing makes you more prepared and confident.

Additionally, it enables you to plan and make more customer-oriented decisions.

SIMPLIFIES DATA PRESENTATION:

It allows you to present data in a visual form that is easy to analyze. Often, the amount of data collected is overwhelming, and sorting it can be time-consuming. Moreover, collection and categorization become easier. This helps prioritize more accurately.

IMPROVES ADVERTISING:

Advertising is a mandatory part of marketing, but useless ads won't help improve marketing. They need to be engaging enough to satisfy different audiences while fulfilling their purpose. To improve advertising, you need to consider market trends. Big data helps you gather meaningful information to enhance ad quality.

4 Ways to Make Better Decisions Using Marketing Data:

Using data-driven marketing is important to increase conversion rates. To help you make decisions, we've compiled 4 ways to make better decisions.

USE DATA FOR CRITICAL DECISIONS:

Sometimes forecasting and decision-making become critical. Clouds of confusion obscure our minds and block decision-making ability. Elements are also ordered based on past achievements. Similarly, you can analyze your past results to decide when to start, what to set, and other common questions to plan your moves effectively. Analyzing past results reveals your weaknesses, strengths, and least popular campaigns. Using previous information, you can avoid repeating those mistakes in the future.

DETAILED ANALYSIS OF PAST RESULTS:

It's important to acknowledge your mistakes and least appreciated campaigns in order to improve them in the future. Additionally, using data allows you to describe past results and identify traffic/campaigns that yielded positive outcomes. Data-driven marketing enables strategies that significantly increase market share and eliminate errors that could attract danger.

BETTER WAY TO EXPLORE NEW OPPORTUNITIES:

It allows you to explore new opportunities for targeted campaigns with higher conversion rates. It allows you to set prices based on past analytics. For example, what is the price of best-selling items? Comparing opportunities helps find new ones.

ANSWER FREQUENTLY ASKED QUESTIONS:

The most common questions when launching new campaigns are always the same: where, when, why, and how? Analysis of the past can answer these questions. However, the location of your campaigns is crucial and depends on the number of consumers in that region. It is often considered as the store location or placement.

Is Your Marketing Strategy Based on the Right Data?

The right data refers to data that is correct, suitable for its intended purpose in planning, operations, decision-making, and relevant. One of the main reasons for rapid business market growth is obtaining accurate insights from data and integrating them into all actions. To develop a professional marketing strategy, you must consider the real conditions that the brand data is supposed to describe. Otherwise, if information is collected without regard to its long-term impact on business and actual results, it will lead to poor decisions. For example, if data misleads a marketer into thinking their buyers are mostly children, while they are actually mostly women aged 20+, then advertising will target the wrong group. Additionally, if your data is not relevant to marketing, it won't help. Avoid collecting irrelevant data. For instance, Pizza Hut knows its audience likes more spices on pizza, which may not be useful for many companies, but it helps Pizza Hut in content development and promotions. The timeliness of information availability is also significant, as outdated data leads to steps not aligned with current realities. Thus, good data collection for a competitive market means knowing your target customers, their preferences, and demand, which ultimately leads to better business performance. In the end, sales and profitability increase. Strategic marketers who incorporate quality data into their pipeline stay ahead of competitors. Your project's location also significantly impacts marketing. For example, if you want to launch leather jackets in a place where winter hasn't arrived yet, why would anyone buy leather jackets in summer? That would nullify your efforts because your product won't be popular. Product price also plays an important role; it should be set by studying best-selling items and determining their price range. In the future, comparable prices should be used to achieve the best results.

How Proxies and Data Extraction Help Make Better Marketing Decisions:

Proxies are servers that filter and forward your request to a website. They allow you to hide your identity by masking your IP address and make mass scraping possible without getting banned. Additionally, they allow you to change geographic location for more thorough research. Data extraction involves collecting useful information and using it to make better decisions. To make better marketing decisions, you need to conduct proper research and gather detailed information about all market developments to stay on top of all trends.

To track a competitor's activities, you need to visit their site repeatedly. This increases the risk of being banned, as a high number of requests from one IP is not optimal for any site. Therefore, when researching, you need to use proxies, as they allow surfing. They remove this limitation by using a different IP address each time. It helps in keyword research, as it's a crucial part of content optimization. You can find keywords on competitor sites and use them for your own web page through data extraction. It's hard to judge which product will be most popular, but with data extraction, you can easily learn about current market trends. Business owners sometimes don't need localized results if they want to go global. When surfing without a proxy, results are localized according to your location. Proxies can be a great tool for removing geographical restrictions.

DATA EXTRACTION TOOLS:

Import.io:

This is the best data extraction tool available on the market. What's more interesting is that it doesn't require coding to extract data, which is difficult for novices. There are various types of web scraping tools available online, and scrapers should know about them if they want to scrape professionally. Tools like Import.io, HTTrack, Wget, Node.js, and cURL can be found.

OuTWiT Hub:

Extracts only relevant data and categorizes it. Ideal for SEO, email, etc. This technique is useful when someone wants to extract data from a website. You can also use the IMPORT XML command to check if your site is protected against scraping.

OctoParse:

This program allows you to extract data from any site by simply typing the URL of the desired web page. Another feature is the ability to rotate your IP address to prevent getting banned. A scraper can use this feature to extract data and information from websites. This technique is useful when someone wants to obtain data from a website.

ParseHub:

Allows scraping sites with login restrictions and infinite scrolling. Scrapers typically use ParseHub when they want a detailed view of a site's structure. Additionally, scrapers use ParseHub analyzers to collect tags containing data and then apply tools like XPath to perform web scraping. Internet Explorer and Firefox are commonly used for scraping.

Email Parser:

It can extract data from emails and doesn't require special coding. It typically collects data from linear or nested HTML pages. This method is usually used for extracting texts, links, and emails, screen scraping, and resource extraction.

Conclusion

With rapidly evolving technology, marketing methods also evolve. Companies now analyze data in real time using big data, giving them an edge over competitors. Big data is very important for digital marketing because it can process vast amounts of information much faster than any human could. But the problem lies in data quality. If data quality is poor, the trend results will be unreliable. And if you want to target a specific segment, too much filtering will be required due to unnecessary information processed by big data. If the obtained information is accurate, various strategies can be derived to influence the appropriate audience.

Knowing customer needs or where the paradigm is shifting is a huge advantage for businesses. It allows them to prepare for changing trends and provide what is needed before others. Data-driven marketing is far better than judgment-based marketing (using gut feelings). Using data-driven information is based on actual buyer trends, not marketers' assumptions. You can also use a proxy server to help target markets outside your region. Collecting data without assistance via VPN is another achievement of new systems. It allows free browsing and maximum data collection without fear of being blocked. Thus, information is very important for marketing. However, if this information is not used properly to develop a strategy, it can lead to potential failures. Last but not least, verify the integrity of the data you work with, because if you work with unreliable information, it can lead to disaster.