Growth

Data-Driven Approaches for Electronics Revenue Growth

By Ashutosh Kumar

Looking for effective revenue growth strategies for your electronics business? Read on to learn how to leverage data to form such strategies.

Relying on intuition instead of data-driven insights can impact revenue growth. The downfall of Hitachi proves this. It is a Japanese electronics giant that used to compete with Panasonic and Sony but failed. Why?

They changed their manufacturing set-up and started creating high-priced products. They did not realise that the consumers don’t prefer high-priced products.

In this situation, gathering relevant data about consumer preferences would be important. Also, leveraging that to make company decisions would have turned the tables around.

Read on to learn how a data-driven approach can help electronics brands. It is useful for revenue growth management and making informed decisions.

Data-Driven Decision-Making for Revenue Growth for the Electronics Industry in India

Revenue growth in the electronic industry in India is complex. It is not a straightforward approach because it is data-driven

It is a long-term process with one strategy leading to another, with the goal of revenue growth. 

Let's analyse how data-driven decision-making boosts profits in India's electronic manufacturing industry.

Better Customer Understanding to Create Customer-Centric Products

Customers are the ultimate source of revenue. But how do you create customer-centric products? 

The electronic manufacturing industry tracks how their products are performing in the market. If customers like it, they make more products. They do this to meet their target audience's preferences.

They can do so by gathering customer data from the following sources:

Website
Surveys
Social media
Cookies
Third-party data providers, etc.

Data gathered from a survey might give you valuable suggestions. For instance, senior citizens may not prefer technology-heavy products. This will help businesses create products using fewer resources.

Thus, the revenue growth of electronic companies soars as they reach a wider audience.

Enhances Manufacturing and Maintenance Operations

The data-driven approach enhances manufacturing and maintenance operations. Collect and analyse sensor data from production equipment. This will help companies identify inefficiencies and opportunities for improvement. This leads to revenue growth in the consumer electronics industry.

Before equipment failures occur, they can put preventive measures in place. Data insights also allow inventory levels, supply chain, and production scheduling optimisation.

This leads to lower costs and increased output for the electronics manufacturing industry.

Optimising Service Delivery

Electronic companies can track service calls, customer complaints, and usage patterns. They do this to identify systemic issues. Data insights allow them to dive deeper into the issues. This helps them solve problems and improve customer satisfaction.

Analytics can also help segment customers and offer customised service plans. Companies like IFB, Voltas, and HP incorporate data-driven support to improve after-sales service.

Optimising Sales and Distribution

The consumer electronics industry tracks sales across areas, channels, and segments. They do this to perfect their supply chain. This helps in inventory management, boosting revenue growth.

It allows the information technology and electronics industry to adjust the numbers and types of products needed at local stores. It also allows identifying locations for new retail outlets.

Steps to Leverage Data Analytics to Form Strategies and Decisions

Data is paramount for electronics revenue growth. But how should a business leverage data analytics? They need to create strategies and make decisions for long-term revenue growth. 

Here are the steps to gather and use high-quality data to form revenue growth strategies.

Step 1: Create a List of Probable Revenue Generation Sources

Businesses must have an idea about revenue generation sources. It can help them with resource optimisation and revenue growth.

For example:

The sale of products and service charges will likely be the most significant revenue source for the electronics manufacturing industry.

Step 2: Identify Data Sources and Gather Relevant Data

With the hypothesis ready, the next step is to identify the data sources and gather relevant data. The data should be able to provide real-life insights about the theory.

Businesses can gather data from surveys asking questions about audience preferences. They can conduct surveys offline in malls or restaurants. Consumers could complete them online via social media platforms and emails. 

A (smartwatch) survey could ask questions like-

Do you have a smartwatch? If yes, do you believe it provides value for money? If not, what is stopping you from purchasing one?
Is it worth spending more than Rs. 6,000 on a smartwatch?
What amount are you willing to spend on a smartwatch?

Step 3: Structure and Present Data

The next step would be to structure the data in a way that's easy to understand.

The team can leverage interactive tools to present the data in a valuable manner. These can include maps, charts, online productivity tools, and PPTs.

Step 4: Conduct Rigorous Data Analytics

Once the data is well structured, the data analyst team can use these analysis methods. This will help them make an informed decision.

Predictive analysis: Predictive analysis means analysing current and historical data, patterns, and trends. This helps to predict the future outcome of a particular action or decision.
Prescriptive analysis: Prescriptive analysis uses processes and tools to analyse data. It recommends the best course of action or strategy.
Inferential analysis: Inferential analysis compares data between two target groups. This produces general analytical results.

Step 5: Draft Informed Strategies

The team can then develop a draft of effective strategies for revenue growth. For example, they can launch a product on a small scale and run a pilot study. Before incorporating them on a large scale, businesses must test strategies.

Final Thoughts

Data-driven approaches for revenue growth in the Indian electronic manufacturing industry are complex. It requires identifying gaps. Next, look for data sources and organise data in a structured manner. Finally, use that data to produce revenue growth strategies.

Businesses can contact data analysis experts like Growth Jockey. We can create a personalised revenue growth formula. Our team of experts operates in every field. This includes the information technology and electronics industry.

We help brands leverage technology, data, and effective marketing techniques for growth.

We focus on sustainable marketing practices, marketing automation, and remote work optimisation.

FAQs

1. What data infrastructure should you invest in to make better data-driven decisions?

Businesses seeking revenue growth via data-driven decisions should invest in data infrastructure. They should-

Invest in a data warehouse to store high-quality data.
Hire a team of data analysts to analyse a large amount of data.
A team of specialists that can communicate the data analysis to the stakeholders.

Brands can also partner with revenue growth companies. Growth Jockey, for example, helps brands use data-backed revenue optimisation techniques.

2. What are the challenges associated with data-driven decision-making for the electronics industry?

Data-driven decision-making has a few challenges for the consumer electronics industry in India.

Lack of access to technology that can help gather valuable data.
Data security and privacy concerns when handling large amounts of high-quality data.
Gathering skilled analysts is difficult. They need to leverage AI tools and cognitive abilities to produce valuable strategies.

3. Apart from revenue growth, what other benefits does the data-driven approach have?

Apart from revenue growth, data-driven decision-making can help brands:

Save resources (like time and money) spent devising and implementing futile strategies.
Maintain brand transparency and consistency in customer experiences.