What would businesses do without data? No matter what niche you’re in or how big your company is, there isn’t a doubt that you gather and store a plethora of data every day. However, this isn’t good enough, because when it comes to data, the most important thing is how it’s used.
By now, everyone should know the importance of data analysis. But unfortunately, most companies only analyze 12% of the data they have and the rest of it mostly sits in repositories. The biggest issue here is that companies aren’t sure of the best ways to analyze all of their data.
That’s why we’ve collected the best tips for data analysis you can use starting today.
Define why you need data analysis in the first place
Data can be collected from multiple places and used for various purposes, but before you start collecting and analyzing your data, you need to know why you’re doing that in the first place.
Most of the time, businesses collect data to solve a problem or answer a question such as:
- How can we reduce the cost of production but keep the quality of the product intact?
- What kind of relationship do customers have with our brand and do they perceive our company in a favorable way?
- How can we use our current resources to increase our sales opportunities?
These are some of the most common questions businesses are trying to solve with data analysis, but you can use data to solve any query you have. And once you know what your purpose is, you should identify which metrics you need to track so you can achieve your purpose.
Even though this process might be long and tedious, it’s necessary if you want your data collection and data cleaning to go as smoothly as possible.
If you already store your data on Google Cloud Platform, you need to use a cloud data warehouse that is leveraged by data analysts as well as data scientists, and that is BigQuery. BigQuery is a new way of storing and analyzing data that comes from data sources and it utilizes the power of Google Cloud Platform.
It comes with the ability to handle many different types of data, comes with accelerated insights, and a very user-friendly platform.
There are four different queries you can perform with BigQuery:
- Partitioning by date. Extract your campaign data from each of your data sources for a specific month and combine them into one table that will provide you with a multi-dimensional view.
- Multi-channel reporting. Other platforms usually contain data in separate tables, which leads to different reports from each platform. BigQuery, on the other hand, utilizes multiple sources of data into one report and blends the data effortlessly.
- Cross-channel reporting. Sometimes you will need to compare your metrics side-by-side to get a better understanding of them and the best way to do that is to merge data from multiple tables. This is easily achieved with BigQuery that offers a multi-dimensional view of your operations.
- External tables. Sometimes you won’t be able to extract your data automatically and will have to deal with Google Sheets spreadsheets. Luckily, you can also load this data into BigQuery and link the manually maintained spreadsheets as tables that can later be used.
But before you can start using BigQuery, you need to extract, transform, and load your data. In other words, you need to use one of the best BigQuery ETL tools and choose it according to your resources, business, and technical expertise, if you want to get the optimal results.
Collect data from LinkedIn
Even though LinkedIn isn’t the most popular social media network, it is the only business-related social media network in the world. It currently has 722 million members and a plethora of useful data that’s just waiting to be analyzed.
There are many different analytics metrics you can track, and the ones you choose to keep an eye on will depend on the goals you set. However, if you’re looking for the best metrics to track, you should consider the following ones:
- Visitor metrics. Track your unique visitors from the Visitors Analytics dashboard to keep up with how many individual people have visited your business page. And if you want to see the total number of times anyone has visited your page, you can do that by using Pageviews.
- Visitor demographics. Learn about the different types of people who visit your page to get an idea of who your customers are and if they fit the idea of the target demographic you already have.
- Follower metrics/demographics. Unlike visitors who are just interested in your company, followers are the ones who are looking to stay connected. You should also track their metrics as well as their demographics just like with visitors.
- Competitor companies. You need to keep an eye on the companies which are similar to yours to see just how big of a threat they actually are. Track their total followers and compare their number of new followers and updates as well as engagement rates to your own.
But to get as much valuable data as possible, you should start with a good LinkedIn campaign and reach out to make connections. The best and easiest way to gather as many people as possible is to use a LinkedIn automation tool. With it, you can expand your network, send automatic messages, invite connections, and much more.
Choose your type of analysis
The data analysis process consists of multiple steps, but the last and most important one is the analysis itself. There are various ways you can analyze and manipulate that data, starting with data mining.
Data mining is defined as knowledge discovery within databases and it uses data mining techniques that allow you to unveil patterns in data that were previously hidden. These techniques include clustering analysis, association rule mining, and anomaly detection.
BI and data visualization software technologies are of great use to business users and decision-makers. When you use this type of analysis, you can generate easy-to-understand reports, charts, dashboards, and scorecards.
Data scientists nowadays can use data to predict future trends and how their company is going to operate in the future thanks to predictive analysis. This type of analysis tries to forecast the most probable next step when a business problem or a question occurs.
Analyze the data from your marketing campaigns
There are many ways to enhance your marketing strategy, but a data-driven campaign is the best way to attract the right type of customers. If you know all of your target audience’s pain points, goals, challenges, and behaviors, you will be able to create a perfect campaign for them.
And when you create a data-driven campaign, take the time to analyze the data you received from the campaign itself to further your marketing research. And if you manage to analyze the data in the correct way, you will be able to:
- Personalize each campaign to cater to the customer-centric experience consumers are looking for.
- Enhance the customer experience through customer satisfaction surveys and other data.
- Optimize all of your marketing channels and run the best types of ads on them.
Before data analysis, companies needed to work twice as hard to achieve worse results than modern companies can achieve nowadays. If you’re smart about your data and know how to use it, these tips you just read about will make your data analysis even better than before.