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Vision-Driven Marketing: Convert Vision into Decisions?

Industrad says that insight-Driven Marketing is the extraction of insights from data analysis that contribute to making rational and actionable marketing strategies. For example, when the Internet service provider company obtains data such as restarting the customer’s communication device (router) more than 10 times a day, the customer service representative calls the customer to inquire if he is facing a problem and how to help him solve it?

What is Insight-Driven Marketing?

Vision-oriented marketing has a core philosophy that successful marketing is that well-planned marketing. To achieve this, two components must be combined, data and human thought. Industradgroup insight-oriented marketing is less concerned with data mining than with using this data to generate insights and ideas that translate into real-world marketing decisions.

industrad - industradgroup
industrad – industradgroup

Vision-oriented marketing has emerged as one of the modern marketing trends to provide organizations with innovative and smart solutions. The advantages of this marketing trend have varied with the advent of the era of big data, and the promises of control and influence on all future decisions, so that adopting it becomes a necessity rather than a feature you provide to your company.

And because the starting point for Insight-Driven Marketing is data, it is certain that companies that rely on data and analyze it to come up with new marketing insights will gain a competitive advantage over other companies in their industry, especially if they use appropriate artificial intelligence solutions to come up with quick insights into the future.

How do you use insight marketing in your business? – Industradgroup

Insight-Driven Marketing depends on the mindset of planning and analyzing data, and converting outputs into practical solutions that ensure the achievement of the company’s goals in the future, and data is indispensable to reach the best decisions and correct practical solutions. However, how can you start implementing this command yourself in your organization or in your company?

1. Prepare a correct database

Vision-oriented marketing relies on getting the relevant, correct data and organizing it in an efficient manner, so the marketer should ensure that the company’s database is ready for the task and meets the following four conditions:

Comprehensive numeric data – Industrad

A company needs to collect detailed data to optimize its marketing strategies as much as possible. This data may include contact information, gender, location, academic qualification and work, history of purchases, as well as interests, preferences, and social accounts. In addition to other non-traditional data such as data related to customer behavior, such as phone calls with customer service, or the total number of miles that the customer has traveled for the car insurance company.

Revised and structured data

Correct data must be accurate and up-to-date, and customer data is usually viewed as outdated if they haven’t made purchases or interacted with the brand during the last several months. However, in Insight-Driven Marketing, data is aging faster than that, so procurement, behavior, and interaction data need to be constantly updated immediately or almost instantaneously.

The database also needs cleaning from time to time. For example, the periodic messages sent to subscribers who have been idle for some time, revealing whether this customer’s data deserves to remain in the database or not? It should be deleted if the customer does not respond after a few tries. Regular revision of the customer list helps produce relevant insights and makes data more manageable.

After collecting and refining the data, these different streams should be combined in one place to manage them, called the data management platform, and it is a central platform that enables companies to collect and organize public data, whether first, second, or third party data from any source via the Internet or the phone.

2. Use the data gradually – Industradgroup

Marketers spend countless hours collecting data, perhaps without a clear strategy to employ this data in the decision-making process, a recurring scenario that causes them to become mentally overwhelmed and end up returning to making decisions based on intuition and assumptions.

In order to get out of this closed circle, gradation may be an appropriate solution, start with a simple set of data sources necessary to make a rational decision and rest assured that they have a proven impact in order to achieve small successful results, then devise from them a vision followed by action on the ground, then include Incorporate more additional data sources over time.

3. Analyze the data – Industrad

Analyzing data in vision-oriented marketing means examining data with the goal of generating valuable insights, not just identifying the increase in sales numbers. That is, analysis that results in discovering actionable ideas and brilliant insights that push the company’s performance a step forward. The analysis should highlight data that improve revenue, not just those that are easy to measure.

For example, when Dutch Network for television services discovered that a large proportion of the company’s sales are via phone calls compared to those that take place over the Internet and that nearly half of new subscribers contact a customer service representative before purchasing the service; For this, I placed the analysis of telephone conversations a priority, and as a result, the conversion rate increased by 60%.

Although it is easier to measure email open rates and website visits, insight-oriented marketing intensifies interest in analyzing activities that translate into sales, which has meant for Dutch Network to analyze phone calls in the same way that any other digital activity is analyzed.

4. Employ machine learning solutions – Industradgroup

Machine learning is a type of artificial intelligence that allows computers to learn without explicit programming instructions. Machine learning reveals important insights that make the analysis picture more complete and provides an important context for studying data. For example: Suppose you want to know which pages are performing the best on your site, traditional solutions will tell you that pages A and B are getting the most traffic.

However, results may differ completely if the scope of the analysis is narrowed to a specific country. Machine learning can tell you that pages (A) and (B) are doing well in Saudi Arabia, while Page (C) performs better in Egypt, machine learning will reveal insights that were missing from you and allow you better planning to optimize the performance of your site pages on sites A different geography.

Other tools that use machine learning technology are those that scan social networks and news sites in search of positive and negative opinions about brands such as YouScan and BrandMentions, and on the Arab level, similar tools are developing to scan content written in Arabic.

5. Create customized marketing messages – Industrad

One of the main goals that visionary marketing seeks to achieve is to send personalized messages relevant to customers, as it has a deep interactive effect that creates a unique and valuable experience that enhances customer loyalty to the brand.

Personalization requires insight into the data and crafting more than one buyer personas. For example: Suppose a store notices that the customers who are candidates for not buying again are divided into two personalities: the first is a customer who buys many products from different departments, and the other is a customer whose purchases are limited to the sportswear section. Thus, each of the two personalities needs different marketing content that suits their buying behavior.

Personalization may take other forms, including: The offers fit with the customer’s interests, preferences, shopping habits and any other information you know about him. It also means not to customize email marketing campaigns based on the type or country of the recipient only, but rather to extract insights from the data telling us whether email marketing is the best way to reach this customer or not in the first place.

6. Adapt quickly to any change in data – Industradgroup

Returning to the revision issue that we referred to in the database terms, Insight-Driven Marketing uses the refined data to map out the interactions that should occur with the customer to help the company avoid wrongful behavior with him. Suppose a customer recently purchased a product and reported a complaint to customer service.

Under normal circumstances, the customer will receive within a few hours of the purchase process a message on his e-mail inviting him to leave a review and write a review about the product, but if the customer’s data has been updated and insights are extracted from the result of his call with technical support and it is quickly adapted You will be able to stop sending this automatic message that proves that the company is unaware of a customer’s complaint and will save your brand to add a bad review from an unsatisfied customer.

It is no longer sufficient to act as the only observer and tracker of digital data, but in the rapidly volatile economic environment overnight, the decision-making process should be based on facts and data affecting revenues, which opens the way for visionary marketing to use and analyze that data intelligently to reach To insights that penetrate the entire investment life cycle from planning to evaluation.

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