The field of big data analytics has been in its infancy for decades, but it's already deeply integrated into the business world. From A/B testing to email marketing, data-driven decision-making drives the success or failure of businesses and consumers. What's more, companies like Google are expanding to keep up with all the changes and opportunities presented by this burgeoning industry. But, questions remain.
What aspects of data report analysis are the most valuable? And how can the field grow to meet the needs of businesses?
Perhaps the biggest question of all is, what is the difference between reporting and analytics?
Answering this question is easy enough, but it begs some questions. Who needs both? And who doesn't need either? To answer these questions, let's look at the purpose of each.
What is reporting
Reporting is the general organization and summary of your data.
It refers to any time you pull data from a service you use to track your marketing efforts. For example, if you are using Google Analytics to track the performance of your website, setting up a custom report is a form of reporting. Doing so requires no or very little analysis on your part because the data has already been processed for you, and the tool has put it into an easy-to-read format for you.
If you need to dive deep into the data, the process would be considered analytics. If, on the other hand, you just want to see the numbers broken down in a specific way or compared to other numbers, reporting is what you're looking for.
What is analytics
Analytics is the actual analysis of that reporting.
If you're using Google Analytics or another service that gives you a lot of detailed data but doesn't provide reports, this is when you start to dig into the data and find patterns or correlations. Doing so takes some time and effort on your part. You need to sit down with the data and search for meaning. No tool will do this for you.
Simply put, reporting is how to get the data you need to make decisions. Analytics is how you decide what the data means.
Who needs both?
This question has a pretty easy answer: everybody. Every marketer needs data analysis and reporting to succeed online, no matter their specific focus.
You need reporting to see what you're doing right and what you're doing wrong. If you have a social media manager, for example, they need data as well. How much are people engaging with your postings? Are they commenting on your Facebook page? Are they sharing your content on Twitter? You need reporting to find out. The same applies to SEO. How much search traffic are you getting? What keywords are people using to find you? Analytics can answer all of those questions in detail for you.
On the other hand, reporting also needs analytics. If you're measuring all those things, then you need to interpret their meaning. For example, you might see a lot of Facebook activity on your page. Is that good or bad? How does it compare to other pages in your industry? You can find the answers to these questions with analytics.
If reporting is the way to get data, then analytics is how you decide what it means.
What is the difference between reporting and analytics
Both reporting and analysis using company data paint a picture of the current state, the key difference is added value.
Reporting is meant to be an accurate snapshot in time, whereas analytics add value by creating new data to inform a decision.
Enabling good analytics requires good foundational data and establishing which metrics matter to you.
Questions brands should ask themselves when comparing reporting vs analysis:
What type of data is fueling your reporting: Before you even set your benchmark of success, you need to understand what you’re collecting. What types of data do you have currently, and which types of data are you missing from the equation?
What am I measuring and why: Setting key metrics is essential to driving better reporting and analytics. Understanding which metrics matter and tying those back to your overall business goals bolster reporting.
What are my goals: For reporting to fuel good analytics, you need to understand where you want to go. What is the desired outcome not only for a specific campaign but for your business in general?
Moving from evaluation to activation
Reporting provides an accurate snapshot of a certain outcome through a dashboard or an ad hoc report. Analysis looks at data and gives context as to why they’re important. Brands must consider their desired outcome and combine reporting data with analysis to see what is possible.
Rear-view vs. future-focused analytics
When marketers analyze reports, there are two basic schools of thought used. The first is what you might call “rear-view” — the analysis of past data to find trends and learn more about your customers. The other is what you might call “future-focused” — the analysis of current data in order to predict where you will be going in the future.
The “future-focused” analytics approach is a more elegant one because it shows how analytics can be a tool that is both powerful and proactive in helping the business — instead of just collecting and storing data like some kind of filing cabinet. Instead of looking for yesterday’s trends, it looks for tomorrow’s opportunities.
The point is that you need both a standard set of tools and methodologies to start the analytics process. To achieve the first, you need tools that are immediately useful to everyone in at least some small way — no one will thank you for making their job harder. To achieve the second, you need methodologies that allow different people to use and develop these tools differently. .
Mastering digital media measurement
Marketers have a two-fold challenge: Collecting the right data and using it to drive their reporting analysis. They need to know their customers, activate digital strategies to reach them, and measure the impact of that effort.
Why does it matter? Mastering digital media measurement can:
- Lead to better customer experience
- Help attract more customers to engage at the right time and continually form better relationships with existing customers
- Increase ROI
- Improve the reporting experience
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The first-party data you glean provides maximum reach and match for optimization and personalization. As a result, you can tailor every message based on what they need and want from your during that specific interaction.
Effective connectivity is identifying individuals across channels—online and offline—with a unique, privacy-compliant ID. Epsilon CORE ID is the industry’s most accurate, stable, scalable identity resolution to recognize and reach 200M+ U.S. consumers in a privacy-safe way.
PeopleCloud personalizes each person’s journey, using identity to drive better outcomes for individual consumers.
Effective connectivity is identifying individuals who can be reached across channels—online and offline—with a unique, privacy-compliant ID.
PeopleCloud fills in data gaps for clients to see all the data that customers are generating on a partner network securely and clearly.
Do more with Epsilon
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