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Market Intelligence is all about valuable data that is easily available to businesses. This data helps evaluate your market position, understand your audience, identify risks and growth opportunities, understand trends and dynamics, develop effective strategies and ultimately drive the growth of the company.
But what if the data used to collect market information is bad or dirty?
Bad data leads to wrong decisions, annoyed customers, high costs, wrong targeting, etc. Technologies like artificial intelligence (AI) and machine learning (ML) also need accurate data to function properly.
So much depends on data quality, and even more so when it comes to market intelligence. Data-driven companies need to trust their data, but the scenario looks bleak: Around 55% of executives don’t trust their data.
Accurate data requires intelligent collection, filtering, cleansing, validation, enrichment and formatting to make it useful and extract meaningful market intelligence.
Attributes of data used to infer market information
As structured and unstructured data is collected from multiple sources such as websites, social media, and surveys, and in a variety of formats, ensuring the accuracy, relevance, and usability of the data remains a challenge.
Let’s start with what makes high quality data:
- I agree: Data without errors or outdated information, redundancies or typographical errors
- Completely: Data with no missing fields, values, or incomplete information.
- Relevant: Data that is helpful for the goals you have set
- Valid: Data that is verified and validated and therefore trustworthy
- Consistent: Data that remains consistent and conforms to your format
- Real time: Continuously and regularly updated data
Why data quality is important for market intelligence
High quality data is a prerequisite for effective market information. Below are six main reasons for this.
1. Better target group approach
Bad data leads to wasted time, energy, and labor as you never connect to the target audience. High-quality data provides orientation so that you can focus your resources on goals with high potential.
Broadly targeting based on guesswork is wasted effort; You are chasing customers with no interest in your services or products. With the highest quality data, targeting becomes easier and more accurate, and marketing efforts become more focused and effective.
Your company knows your target audience and you can even find potential targets with similar characteristics. Defining your goal based on demographics, preferences, and behavioral patterns is a critical starting point for your marketing efforts.
2. Build effective campaigns
Once you know who to contact, you need to plan your campaigns for meaningful targeting. Quality information about your audience enables you to create relevant campaigns and develop powerful content that speaks to your goal. Knowing your target’s preferences, age group, income, and any other relevant info can help you create effective campaigns that will get the desired response from your audience.
3. Personalized messages
Access to high-quality data on personal data such as demographics, preferences, etc. helps you to send targeted personalized messages to your target audience.
People expect a personalized experience and are dissatisfied when there is no personalized message. A whopping 80% of consumers are more likely to do business with a company if they have a personalized experience, and 90% say they find personalization appealing, according to an Epsilon survey.
High quality data and personal information improve communication and enable you to send tailored and relevant content to your target audience.
4. Build better relationships with your customers
Sending personalized messages helps, but when you get access to more personal and accurate data about your target audience, you can go a step further and anticipate their needs and plan products, services and unique content specifically for them. This will help build stronger and better relationships with your goal and ultimately help your business grow.
However, this is a tricky situation and data management is a necessity. The data should not have duplicates or missing fields. For example, if the same person receives your message twice, they get upset and can ruin your relationship.
5. Competitive advantage
The cost of bad data is around 15-20% of a company’s annual revenue. This is a significant loss and affects the organization’s credibility. Ensuring the quality of your data gives you a competitive advantage over your competitors.
In addition, collecting intelligent information about your competitors will reveal what they are or are not offering. You recognize the differences and plan your long-term business strategies accordingly. You can anticipate things and discover opportunities before your competitors do, act quickly, and advance in the race.
6. Create trustworthy insights
High quality data is critical to the advancement of AI and ML. Most data-intensive automated projects fail because of poor data quality. ML is growing in popularity and is badly needed by companies to generate meaningful insights.
Analytical advances, AI and ML are advancing rapidly, but the technologies are of no use with poor data quality. Extensive, accurate, and complete data is the key to accurate results. A computer algorithm that works on bad data can produce seriously erroneous results.
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The information age is bombarding us with amounts of data. Efficient use of this data is only possible if it is well managed and effectively used to gather market information.
Most important is the data quality. Accessing high quality data is like finding a gold mine: you will target precisely, make informed business decisions, create effective campaigns, build better relationships with your customers, stay ahead of the competition, and ultimately make big profits.
More data quality resources
How bad data hurts B2B companies [Infographic]
The most important ingredient for the success of marketing campaigns: quality data
A five-point plan for first-party dates
