How Brands use Data to Enhance Consumer Experience
Big Data Applications

How Brands use Data to Enhance Consumer Experience

Every industry boasts of a plethora of brands battling for a higher market share! You turn to consumer electronics and we have the likes of Apple, Lenovo, HP and Dell among others fighting for their reputation among customers. In the automotive world, Maruti Suzuki, Tata and Mahindra & Mahindra battling it out with many others to thrive in the market. 

So, how do these brands manage to keep their game up? How do they even determine what their next objective is and what their strategy should be in this game? All these answers lie in what their customers believe and feel about them. In other words, they need to closely monitor the sentiment of their customers.

Brands have become intelligent in the way that they place their customers at a high pedestal and listen to their opinions. Your customer is a huge and valuable source of data that you should pay utmost attention to. It helps you monitor your customers’ sentiment among other things. Let us see how brands monitor customer sentiment to enhance the customer experience.

What data can your customer give you?

Your customer often knows what he needs/wants. They can help you understand their needs if you pay enough attention. Customers not only generate data about their demands and purchases but also latent information about their preferences, decisions, and journey through brands, products, and industries.

A customer can be your source of big data spreading over various horizontals. You can use this data to monitor your sales data, design your marketing strategy, customize your product and service offerings or even get insights on your supply chain and operational processes. This data hence generated gives you a 360-degree view of your customer. Some of the basic datasets that you can gather from your customers are as follows:

1. Sales and purchase data

 Irrespective of the industry you operate in, if you have products or services to sell, your customers will make several purchase decisions. These decisions when monitored and recorded will give you different trends for different demographics, geographies, time periods and even products.

You can use this data in its granular format i.e. at the transaction level or even aggregated/rolled-up format. You can aggregate this data at any level like store, customer, product, geography or even for varying time frames. This data can be used to solve various problems like product portfolio optimization, sales forecasting, customer segmentation among many others.

2. Customer sentiment data

Most online retail sites have a section for customers to type in their opinion and feedback on the product. They even record their experiences with the services in these sections. This is a direct source of your customers’ opinions and sentiments.

However, for a lot of industries and domains, you need alternative datasets to gauge your customers’ mindset. For instance, a lot of manufacturing companies use data from public sites and forums including social media sites to monitor consumer sentiments towards their products and even grievances and complaints to find areas of improvement.

A lot of service-based companies also rely on social media data. You can also monitor a customers journey through various service aggregators depending on the industry you belong to. For instance, if you are in the hotel and hospitality industry, you can gauge how a customer feels about your organization from his browsing and decision-making process on aggregators like MakeMyTrip or Goibibo. You can use this data to improve your products and service offerings.

3. Customer lifetime journey

You can obtain your customers’ demographic details, their loyalty, and affinity towards your brand from various sources. The most common source of this data would be your own customer database coupled with sales trends data from the market/industry and if possible, your customers. You can evaluate your market share using this data. You can also use it to segment your customers based on their journey with you and their loyalty towards your brand. This can also help you identify the set of customers you want to target for your next campaign or product launch.

4. Customer technical footprint

A lot of brands across industries are monitoring their customers’ technical footprint. This gives them an idea about the demographics of the users, their choices and even gives you an insight into their behavior. If you have an online presence and interact with your customers through an online portal, it would be important to monitor the activity on all these forums. You should be able to compare the performance of your website and your app if possible.

A lot of key trends like the usage across the day, metrics like click-through-rate, conversions, drop-out rates, etc. are very vital to your digital strategy. It can help you develop online content to intrigue your customer even further. It can also help you design strategies like when to roll your next campaign out, what offers to provide to your customers or what products to cover under promotions. It can also help you design personalized recommendations for your customers based on their respective preferences.

While the above are just examples of the many data points you can obtain from your customer and the many things you can do with all of it, the actual possibilities are endless. If used creatively, you can use your customer data for not only your online strategies but also for your offline presence.

Also Read: Boost E-commerce Growth and Brand Reputation Using Customer Feedback Data

How do brands use this customer data to improve customer sentiment?

Setting up the data system

The first step in the process of using customer data is to establish a data-driven system. Your organization should instill a data-driven behavior in all your operations. This will need a well-integrated information system and IT (information technology) infrastructure. You need to identify the different kinds of data elements you want to capture and their respective sources.

You then need to categorize the data elements and identify which horizontal in your organization needs which data point immediately. This will help you create the required compartments and integrations in your data systems as well. While you do this, you should also ensure you are not exploiting your customers’ privacy or violating their safety. While you have access to all their data, it may be unethical to use this data for your strategies if you use this against them for your own benefit.

Once you have identified these data elements and sources, you need to set the required infrastructure up. For instance, you need to set up the proper gateways, servers and information systems required to capture and store your customers’ digital footprint. You then need to integrate the various systems into a central system with the necessary authorization protocols put in place. In this process, perhaps you will also realize that you should isolate some data streams instead of integrating them as well. This will be one of the most crucial steps. You should note that the maintenance and security of these data systems should be constantly updated and taken care of.

Use data as a service- not just an entity!

As discussed above, data can help you optimize and improve your existing processes and invent radically innovative operations. You thus need to use data as a service. By this we mean, you can probably share your data elements with companies that create and provide analytical solutions. This will not only help you learn about your own performance but also compare the market trends and competitor performance. It will help you gauge the customer sentiment better and design strategies to improve your customers’ average lifetime value.

You need to collaborate with partners and identify the data sources you can share with them. In exchange, you even might want to get access to some secondary data sources that you may need for your analysis. For instance, if you are in the retail business, you may want to collaborate with companies that scrape macro-economic data on fuel prices or even GDP. This will help you improve the supply chain processes or decide your budget for the next fiscal year.

Use data to drive action!

As discussed above, you can use customer data for a wide array of purposes. While you can use structure datasets (i.e. sales numbers or customers’ digital footprint) as is, you might need to preprocess and treat your secondary unstructured datasets (for instance social media data) before you can analyze the same. You can use your data to learn what your customer wants next. You can use these insights to design content or products accordingly if you are in the relevant industry. For instance, if you are in the publication, media, and content development industry, your customers’ profiles and their opinions will help you tailor your content for maximum subscriptions or retention.

You can use your customers’ data for descriptive, inquisitive, predictive and prescriptive analytics. You can design recommendation engines tailored for each customer individually. This will not only elevate the customer sentiment but also draw new customers in. This exercise will not only help you improve your customer engagement practices but also place you at the top of your industry. Now, investing in data is not a bad option if it gives you that competitive edge, isn’t it?

While you develop your data-driven practices, it is also important to keep a note of the best practices, security protocols, ethical practices and maintenance operations. Breach of the customers’ trust is an unforgivable mistake. It can cost you your brand value and your customer base.

We at Datahut can help you procure the necessary data

Datahut has served a lot of firms across industries procure the necessary data elements in the required format. We can help you set up the required system to stream the required data and store it for further use. We follow a very transparent process and help you solve problems.

Wish to avail web scraping services for your data needs? Contact Datahut to know more

About the author

Srishti Saha

An electronics and communication engineering graduate and a data scientist by profession, Srishti has a passion for upcoming tech and gadgets. She believes that IoT, AI, ML and Blockchain will come together to change the daily lives of human beings. She wishes to be part of this revolution.