Choosing a vendor for data analytics can be a tricky task. Most businesses go wrong in relying solely on the vendor’s pre-canned demonstration. Such demonstrations, based on tailor-made scenarios and predefined set of data create an alluring trap for the unsuspecting customer. The right approach is to evaluate and judge them on the basis of answers to questions that lie in the heart of your business. This way, you get the best vendor for your business, though it may entail difficulties and frustration.

What Questions You Need to Ask to Your Vendor?

You need to do a lot of homework before sitting face-to-face with your prospective vendor. It should pertain to the unique business challenges you are facing basis which you need to frame questions for your vendor. This helps you on two counts: one, you avoid committing the mistake of asking generic questions and two, you get to know how effective the solution can be to the problems you face. Consider this question: how do the traits of customers who purchase for the second time differ from those who purchase only once? This question is more specific, and the answer can give you real insights into some actionable information. You need to ask questions like these against realistic data volumes and judge if the vendor can explain their answers in plain terms and without a fuss or without re-attempts.

If you are convinced, your next task is to probe about the process. Ask the vendor about how they integrate all necessary data sources. This can help you know how they deal with minor or major disasters when handling batch processes for large amount of data. Also, ask them how they deal with poor data quality or missing data. This gives you an inkling into how well they can get things right in the first attempt. Further, you must enquire about their tools and metrics and how the two are used to provide statistically relevant answers. Lastly, check whether the vendor is capable of constructing and sharing a convincing story from these insights.

Why Choose Us for Your Data Analytic Requirements

We believe in demonstrating our ability by using your datasets to provide actionable solutions. We welcome targeted questions as we think it is the best way to clear cobwebs pertaining to critical business issues. Our data integration process focuses only on the data you actually need for your processes and so we start small and then build slowly and thoughtfully. We split parallel and complex data flows to streamline the data optimization process which obviates the need for long wait times between questions. In case of missing data we choose an appropriate method from a string of methods to decide on the best analysis strategy to yield the least biased estimates. Likewise, we have developed a scientific way of dealing with error prone data.

We reject the error when accuracy is more important than completeness. If the error is within acceptable level, then we accept the error.  If the correct value can be determined, we correct the error before proceeding and in case the correct value cannot be determined when completeness is critical, then we substitute a default but logical value for computation. At the end, we compare the results with the metrics to make sure there is proper intuitive sense, and present it before you in a story/visual format to help you understand the findings in a clear and compelling way.

This aside, we leverage some unique tools to capture and manage data as well as remarket to lost prospects.  If your problem is unique we can help you with a customized software solution built to meet your needs.