Marketers face some of the biggest challenges of the modern era ― to curate and use the highest-quality data so their campaigns are successful. However, considering the ever-growing amount of information created and processed every second, identifying what is most important and relevant for a company’s target audience is challenging.
This issue deepened as more companies rely on
AI services and products, which require considerable amounts of data to function accurately. Unfortunately, a lot of information doesn’t guarantee success in a marketing campaign for several reasons that we’ll discuss briefly.
Using data for marketing purposes requires a lot of work, including cleaning and structuring it. In addition, teams must learn to evaluate data quality across various key dimensions, including accuracy, consistency, reliability, and uniqueness. So, let’s see how to do it.
What are some common challenges in data gathering?
Looking for reliable, high-quality data for your marketing campaign might be difficult due to struggling with:
- Incomplete data that requires filling in the gaps, or making assumptions;
- Inconsistent data that leads to poor data interpretation;
- Irrelevant data that’s outdated or unrelated to the requirements for the campaign;
- Complex datasets that have too many unimportant fields;
Considering the difficulties in overcoming these issues, it would be ideal to contact a specialized agency whose teams can guide yours and provide the necessary tools for the research project. For example, experts’ strategies found on the
Clariti website rely on a combination of automated checks and human contributions to ensure that the information comes from high-quality resources and is relevant to your campaign.
Why is data cleaning and structuring so important?
Cleaning and organizing the data can help marketers tremendously by making it easier to pinpoint actionable insights. The system is often referred to as data preprocessing, and it can not only reduce the costs of operating with big data and prevent operational issues, but also provide data ready for analysis.
Some of the steps involving it include:
- Addressing missing data by filling in or discarding incomplete entries;
- Standardizing formats to ensure consistency and smooth out irregularities;
- Eliminating irrelevant data by carefully selecting the most helpful information;
- Removing less important variables by focusing on key data;
How can you evaluate data quality?
After cleaning and organizing the information, it’s time to evaluate its importance for your campaign, a process in which the team will measure:
- The accuracy of the data that is linked to a real-world phenomenon;
- The completeness of the information and its relevance;
- The consistency of the data that comes in a uniform format and structure;
- The reliability of the datasets ensures their trustworthiness;
- The validity of the data reveals whether it represents a concept or a phenomenon;
- The timeliness of the data, meaning if it’s relevant to the modern day;
- The uniqueness of the information addresses its lack of duplicates;
How can high-quality data help you?
Building a marketing campaign as a small, medium, or large-sized company is all about delivering relevant content to your audience. However,
learning more about the audience can be challenging when the era of consumerism and social media is changing trends in a matter of days or weeks.
Therefore, it’s imperative for businesses to unlock the power of high-quality data and benefit from:
- Accurate predictions over future trends and customer needs, which improve decision-making;
- Improved efficiency by removing irrelevant information and generating results faster;
- Opportunities for innovation and growth by uncovering hidden patterns;
- Higher competitive advantage comes from better products and services;
What kind of data should you collect?
As mentioned before, the type of data you use for the marketing campaign matters, which is why the team responsible for this task must manage the collection of:
- Demographic data, such as age, income, and education;
- Psychographic data, such as lifestyle, values, and personality traits;
- Behavioral data, like purchase history and website visits;
- Transactional data, including how often they buy;
- Attitudinal data, from opinions and attitudes towards your brand image;
All this information helps create the customer persona, which enables personalizing customer experiences and connecting with the target audience. Of course, the highest-quality data will ensure you design the most accurate version of the persona through these methods of collecting information:
- Surveys and questionnaires;
- One-on-one interviews;
- Focus groups;
- A/B testing;
- Website traffic analysis;
The ideal plan for data collecting
If you assigned the project to your team, it’s best to offer them a clear objective. The process might vary depending on it, which is why switching from improving brand awareness to boosting sales is not that easy.
The team can work with the tools they already have, such as basic software, or seek assistance from specialized brands. Regardless, data collection software is necessary for gathering web analytics, social media insights, and CRM (Customer Relationship Management) statistics.
Utilizing AI tools is also beneficial, even if they, too, require valuable information to function effectively. Still, AI systems can be considerably beneficial in helping you reach your goal by automating specific tasks that take too much time and could be optimized.
AI-powered data collection is the future
The future of marketing strategies and brand building relies on artificial intelligence. This is one of the future trends that will change the world, as AI-driven tools can process vast amounts of data, even from unstructured documents. In addition, machine learning algorithms can predict trends by identifying patterns.
Big Data analysis will also improve in the near future, as companies will be able to average it for collecting, storing, and analyzing data to discover hidden opportunities. These systems can integrate data from multiple sources, including customer behavior and social media, and utilize advanced analytics to correlate trends with customer needs.
Final considerations
Every organization wants to utilize high-quality data, but collecting it can be time-consuming and challenging due to various operational challenges. A certain part of the information companies gather for their marketing campaigns is either irrelevant or contains gaps that can interfere with the campaign’s success. Therefore, collaborating with agencies that can guide you in collecting the best data for the company or support your team in approaching this task will provide insight into how the data should be processed and structured before being used.
☰
