By now all marketers and advertisers are working with data analytics to determine strategy. Access to consumer data has never been more valuable, or available. From geotargeting to the personalisation of messages, data has taken the concept of tribal marketing to a new level. However, there is more to data analytics than reports produced by Google and Twitter.
Data is information that is collected from your clients when they sign up for your newsletter or your email and they give you their personal contact information, or when someone makes a purchase from your website. Your website traffic statistics are a form of data.
This data can mean very little on its own. While you might see that your website had three hits in an hour, what is more important is how they travelled to your site, what they looked at when they arrived and how long did they stay on your page?
Data analytics is the process of taking raw data and transforming it into something useful, such as identifying trends. Using that information, you are then in a position to better shape strategies for your growth, advertising or even redevelopment campaigns.
Where Does Data Come From?
Big data is all the information you’ve collected, and all the information that other companies have collected, and it’s all stored on clouds and drives, and is bought and sold like fiat currency. However, data without analytics isn’t very useful. Referred to as a data lake, which is a system or repository of data stored in its natural/raw format, usually, object blobs or files, data management takes the data and sifts through it to offer meaningful information you can use to inform your business and marketing decisions. If you know where most of your website hits come from or what content is most successful, you can determine better strategies.
For B2B companies, website traffic statistics are one of the most popular data sources. Others include site registrations, such as the form you provide to allow clients to sign up for your mailing list. Other popular sources include CRM records and customer surveys, qualified online leads, and even syndicated market research.
Making Meaning
Data analytics is the process of making meaning out of the raw data collected. Data on its own means very little. It requires a question to provide answers. The information generated by analysis can then be used to steer business and marketing decisions. If your target market is the EU and most of your hits are coming from Singapore, it might be time to A/B test your site or redirect your advertising.
There are generally two types of data you want to collect.
- descriptive data – which includes personal contact details, employment information and customer satisfaction surveys.
- behavioural data – which includes website statistics, email open rates, and traffic movement.
Predictive Analytics Are Common
Predictive analytics are popular with B2B marketers as they help determine a more robust long-term strategy based on tangible facts.
Using artificial intelligence and machine learning you can analyze large amounts of big data for current and past trends. AI can use this information to “learn” and make predictions about future industry trends. While predictive analytics is limited by extreme events, such as the COVID-19 pandemic, it can be used in more stable times to guide company decisions about growth opportunities and market potential.
Other Uses of Data
Data analysis can reveal future trends and historical associations between trends. Data can also be used as diagnostic, prescriptive, and contextual analysis that can provide insights into your business and marketing efforts.
While using data analytics to inform decisionmaking is common, it can also become an obstacle for those who are overly reliant on statistics. Part of the reason that data can be less useful is the poor management of data, leading to anomalies and variances that might not be relevant and that skew figures.
Many B2B companies work with old or outdated data. This obviously poses issues. If the data you are using to send emails to clients has not been updated in 2 years, you are wasting valuable time and potentially losing valuable goodwill.
Data collection needs to be defined so that you understand what is valuable and what is not. This can be determined by using a CMS that is catered to your business needs, rather than hoping a uniform system will benefit your business.
Ensuring data is uniform and accessible will improve your marketing strategy. Keeping data clean and up to date will ensure you’re working with the best information you have giving accurate insights. The short term work will lead to long-term gains if you take the time to understand how data analytics can benefit your business growth strategy and understand the needs of your business.
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