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If you’re considering an analytics for your business, it means that you’re serious about growth.
The earlier you can incorporate an Advanced Analytical solution into your growth plan, the sooner you can start understanding user behavior and have an edge over your competition.
Here are 4 factors you must consider when choosing the right Analytics Solution for your company:
1. Are You Ready to Take Your Analytics to the Next Level?
Once your business start to grow and user’s digital actions result in millions of data events, you’ll need powerful and dynamic Data Analysis capabilities. These include the ability to analyze raw data and aggregate it from all the different sources, whether it be marketing channels such as Adwords or Facebook ads, mobile attribution like Appsflyer, or even your CRM database.
You’ll want to be able to analyze and reveal patterns in your customer behavior. That means that in addition to being able to store data permanently, you’ll want to be able to analyze both structured and non-structured data over a period of time.
You’ll also want to connect datasets from your main database, with others holding different kinds of data, such as product serial numbers, or financial data, and analyze them as a whole – for example, conversions on your site to emails from your CRM – so that it will start to tell the story of the full customer journey across all touch points.
And let’s not forget about the ability to service multiple analytical apps with real-time analytical capabilities, so that you can react to your users instantaneously.
All of these Advanced Analytical capabilities will help you get the answers you need to complex business questions and move your business into its next stage of high-phase growth
2. Do You Have the Time, Money and Resources to Build and Maintain Your Own Analytics Solution?
Although it may seem like building an in-house solution will save time and resources, the costs of infrastructure, software, and human resources involved can easily spiral out of control.
A business looking to analyze up to three terabytes of data a month, for example, can spend over $900,000 annually for an in-house Analytics Solution!
Remember that it’s not just the setup costs involved, but also additional time and resources needed from your staff for upgrades and new features, as well as support and routine maintenance. The 12- 18 months it takes to get an in-house solution up and running (and keep it running at top efficiency) may be better spent creating a great product.
3. Do You Wish to Monetize on Your Data?
Although there are advanced, scalable and cost-effective Analytical Solutions out there, buying an Analytics Solution isn’t the answer for every business.
Ask yourself whether data and Data Analytics is your company’s core business, or a means to an end.
Are you looking to monetize directly from your data, for example? If yes, then building your own analytics solution is probably the way to go.
If it’s a means to an end, like understanding product placement and online behavior within your site, consider buying.
4. Do You Need an Analytics Solution that is Agile and Scalable?
Traditional business intelligence solutions require a commitment to a pre-planned timetable for growth. They aren’t built to scale. Digital intelligence solutions, on the other hand, are especially designed to start small and grow with your business.
Companies usually pay per number of events sent, or number of queries. Some businesses, on the other hand, don’t pay at all until after going over a certain limit for events. These Pay As You Grow plans can give early stage businesses an understanding of their customers that set them ahead of their competition.
A Full-stack Analytics Solution, Built for Fast Growth
The Analytics Solution a business chooses plays a key role in their growth. You need to take several factors into consideration. First, you’ll have to evaluate whether you’ve reached a point that your Google Analytics is no longer provides answers to your ad hoc questions and you need to move beyond measuring your KPIs. Second, you’ll have to calculate whether you can afford the time and money it takes to build your own Analytics Solution (or whether or not you have data scientists in house). You’ll also need to decide that your product isn’t focused only on data monetization.
Finally, you’ll need to realize that you can’t pre-plan your fast growth, or in other words, that you need a dynamic, scalable and agile solution. If your product fulfills all of these qualifications, it means you are ready for a full-stack analytics solution that adapts to your dynamic needs for data and its analysis.