Ask Smart Questions To Data Analytics And Grow Your Business

Your customers have changed the way they shop, have you changed your focus to use data analytics?


It has become nearly impossible to decide which is faster - the creation of data or the consumption of data. Whichever it is, the investments in data analytics hardware, software, services and service providers, as well as the demand for data scientists, data engineers, and data translators, are growing in leaps and bounds. Convenience in the availability of large data sets is a primary reason why deep learning, a subset of artificial intelligence (AI) has emerged as one of the hottest tech trends today. Google, Facebook, Baidu, Amazon, IBM, Intel, Microsoft, and many others with really deep pockets are watching the space and have made significant investments in acquiring decision analysts delivering data analytic solutions.

Organizations and enterprises, irrespective of their size, are looking to master, monetize and measure their use of data. Business analytics specialists are saviors in this case. They are masters at looking inside the data to gather information and generate actionable insights that help in differentiating business decisions.

Ask smarter questions

To ask questions, you need an information-based strategy. The issue is that you have more information than you could imagine at hand about your business than ever before, but you fail miserably when it comes to using it to 'outthink' competitors. The challenge that you or your business failed at was not with how to gather the data, or data cleansing, or how to structure that data. There are many data management solution providing companies to address such ancestral issues appropriately. You as a business should start asking smarter questions and get to the core of business issues – fast.

What should companies be asking to use analytics to transform their performance and boosted revenue, increase profits and enhance customer satisfaction and retention?

1. How does data analytics improve service level performance?

Take delivering flowers as an example. It exemplifies the granularity which analytics can deliver. Florists use a network of small flower vendors to fulfill orders, along with their own distribution centers as well. Analytics of their sales and customer feedback allows them to predict their ability to identify and meet customer demands. Most of the time, demand is for same day delivery; based on average delivery time concluded through traffic patterns in major cities. This empowers them to not only make but also fulfill commitments made, or pass on business to others for healthy relationships wherever timely delivery is not possible, or propose a next day delivery; the least they can do.

2. What about order fulfillment?

Florists measure success in many shades, based on the time of day, day of the week, products being sold, and whatever festivities may be occuring at the time. Analytics conducted to assess the performance of suppliers helps in identifying which of them provide the best profitability or any order based on location, which ultimately enhances order fulfillment.

3. Does data analytics take care of supplier management as well?

Direct assessment of customer complaints and refund requests, empowered by data analytics, is what will help you drop poor performing suppliers. It may be from on-time or product quality perspective. Ultimately, it helps you to ensure that your clients get good quality of products and services.

4. What about customer value? Does data analytics maximize that?

Data engineers enable you with insights of customers, such as those who will come back for repetitive business. This will empower you to optimize your marketing investments. The florist can go ahead and build long-term relations with such customers to maximize their value, and the level of recurring business along with it.

5. Cost efficiency and data analytics; is it not alienate?

The flower business is very seasonal. Certain days in a month and in a year, such as Valentine’s Day and Mother’s Day and Christmas, are known to have at least ten times the demand as normal days. Meeting such circuits of demand requires a flexible labor force. All that is required to be done is to turn the focus of your data analytics inwards, which will help you improve forecasting and hence staffing, to manage and minimize operational costs.

6. How does the magic of analytics works with advertising?

Your marketing and advertising plans may be A, B, and even C split tested. Your in-house teams would have gone to the extent of assessing the effectiveness of landing pages, pop-ups, and even the product images, with tweaks to ensure maximum results. Product positioning on the website is measured to identify the best location to rocket drive sales and engagement.

But, if you are reading this; you are experienced enough and know that advertising can turn out to be a costly affair at any given moment. Only data analytics can help you get the best return on investments.

7. Data analytics penetrates in product management, is it?

A product or service provider today provides thousands of various products. Only analytics can help understand which ones are the most popular, or may be a combination of products, or a hamper that varies by region and seasonally. Data analytics ensure that the company targets the right product at the right time to the right audience. This eventually helps increase sales and the bottom line.

It's time to strengthen the scale and power of analytics

Companies today are generating more data, and this is because their customers are using more devices to interact with them, increasing the overall volume of interactions. Instead of aggregating that data, our analytics should become more granular of everything from site features to ad campaigns. Customers are changing the way they used to shop and so should we change our focus to use analytics and create the experience for them.


Read next:

Why Blockchain Hype Must End