It can be tricky to monitor the different factors that affect your revenue. For example, if you’ve worked hard to open a store in the mall, you could be wondering why you’re not making any sales. You’ve spent a lot on advertising and building a brand, but why is no one buying? There might be a lot of visitors and customers, but no one seems to get your products. Some factors that might influence this include the very few cashiers, your store’s interior, or the quality of your products. 

To keep tracking more convenient, you can sell and analyze data online. A lot of tools can help you monitor, analyze, and optimize how your business is doing. The internet offers a plethora of platforms to be creative as a marketer. It lets you track every click on and through your website. You do not have to guess which elements are making your campaign successful or not. 

Some important concepts in data analytics include click path, conversion, heat map, key performance indicator (KPI), metric, segmentation, and visitor.

Getting Started with Data Analytics

It has always been possible to understand the responses of customers to marketing messages. However, pinpointing the exact event that happened and its cause used to be tricky. 

During the rise of traditional media, actionable data was scarce and highly sought after. Right now, the digital age allows us to retrieve information anytime at any place. Each action done online can be recorded and tracked. This means that marketers can look at a wealth of data and understand all the questions they have regarding their campaign.

Monitoring Performance and Trends

Monitoring the behavior of users and the overall marketing campaign is central to conducting data analytics. Identifying and analyzing trends is necessary as you don’t want to look only at a single point of data. 

As an example, we can’t draw a conclusion from the finding that 10% of this month’s web traffic converted. We can’t tell for sure if that’s good or bad unless we state that 10% or more people converted this month compared to last month. This means that a single piece of data won’t give a full view of your performance unless it is shown in full context. 

Big Data

Big data refers to massive sets of data that require specialized software and huge computers to process. For instance, Facebook and Google collect too much data every day that they have very big warehouses that hold hard drives of stored information for data analytics.

Data Mining

Data mining is the procedure of looking for hidden patterns in databases and huge numbers. Instead of employing a human analyst who can process the information, the one who pulls apart the data is the computer program. It matches data to recognized patterns in order to produce insights. This process usually shows surprising results and breaks a lot of assumptions. 

Data Sources

Many think that you have to restrict yourself to single web-based analytics in terms of data analytics. The truth is, you can discover and gather data from a different types of sources. This will help you get a wider view of your audience insights. 

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Some data sources to consider include:

  • Databases that contain significant customer information. This may include CRM information, contact database, or loyalty programs. These databases can support anonymous information with concrete demographic insights.
  • App Store data lets companies track and analyze how customers download, pay, and use apps. Google and Apple store are some Marketplaces that can provide useful data.
  • Software data can also be a source of data, such as web browsers that gather information on user habits. They can also collect information about crashes, problems, and more. If your brand produces software, try adding a feature where you gather data that can be used for future updates.
  • Online data shows how your audience interacts with your brand online. This can be found in email, forums, social media sites, and more. These platforms usually have their own tools for data collection.
  • Offline data is simply data that is off the web. This includes point-of-sale records, surveys done on-site, customer service logs, in-store foot traffic, and more. 

Data Analytics Goals and KPIs

Design your online campaign with clear, specific, and unique objectives, and it will surely be a success. Goals and objectives allow you to focus on the activities and measure the success of the campaign. Many think that objectives and goals are just the same. However, they are very different.

The  campaign’s objective is aligned with the business’ desired strategic results. It answers the question, “What should be achieved in this marketing campaign?” For instance, “to increase product sales” is a valid objective, along with growing brand awareness, and increasing website traffic.

What Are Data Analytics KPIs

Key performance indicators are indicators that can determine if the objectives are being attained. The shortcut for this is KPI. There are multiple potential KPIs, so it’s also important to know which one is more important for the campaign. They are just like goals, except they answer, “what should be recognized to see if the goals are being attained?” As an example, if one of your objectives is to increase website traffic, the number of website visitors would be a great KPI. The percentage of new visitors and the length of time they remain on the site are also helpful. 

Lastly, the targets are the main target that KPIs should attain so that the campaign can be considered a success. If one KPI is a newsletter subscription, then your specific target in data analytics can be 100 subscriptions every month. If in one month, you only get 55 subscriptions, this means something needs to be fixed.

Even if a website has the main goal, it takes a lot of processes and steps to achieve them. The term for this is micro-conversions or events. Every step has to be analyzed in the procedure called path analysis or funnel analysis. It’s important to understand where problems in the conversion process lies. 

To track and collect data, you can do it through cookies or a server. Some also use universal analytics. It can transform the data collection and analysis method. Universal analytics, a non-cookie-based serving tracking, is interesting to a lot of marketers.

© Image credits to Adrien Olichon

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