How Data Analytics can help Businesses
In today’s highly competitive age, it is challenging for businesses to sustain and grow. With customer expectations are at an all-time high and competition is continuously increasing, businesses are under constant pressure to increase efficiency and improve results. The focus is on to meet the three most sought-after goals; the ability to reduce costs, increase profitability & improve risk management.
In order to fulfill the defined goals, business need to prepare the business strategy accordingly and take informed decisions.
At the same time, the amount of available data is also growing. Businesses can now collate information from across their organization and industry. This gives them a serious insight on where improvements are needed, where trends in sales have increased or decreased, and where there are potential gaps in the market. It’s therefore no surprise that data analytics has become an important tool across organization for businesses. By bringing together data from across the business, companies can get real-time insights into finance and sales, marketing and product development, and much more. This data enables each team within the business to collaborate better, achieve better results and outsell competitions.
However, data is everywhere and sorting through it to find what is useful and pertinent to the business is a necessary skill to be effective in the current marketplace. The challenge is to understand how analytics can help business and begin to address any issues are most important to short and long-term success.
Here are the areas where data analytics can be leveraged to transform the business performance:
1. Identify Business Opportunities
Data analytics can help in identifying new business opportunities that may have been otherwise overlooked, such as unserved customer segments. Analyzing the collected data or data from industry can reveal the underlying trend such as who are the buyers, what customers buy, what are the gaps in products, etc. These insights can lead to new business opportunities or grow the existing business.
2. Better Targeting Customers
An analysis by McKinsey & Company showed that using data to make better marketing decisions can increase marketing productivity by 15-20%. Businesses can use customers’ details and their purchase history to understand their buying patterns, which can further be used to target the customers, like determine the types of coupons and special discounts to be sent to customers.
There is a lot of information businesses can use for predictive analytics that help improving customer’s experience with the brand. Determining the right tools to examine customer’s buying habits, and implementing them to provide reliable and actionable intelligence can activate buyer instincts and embed brand into customers’ minds.
3. Improve Internal Processes
Through data analytics, business operators can get a clearer view of what they are doing efficiently and inefficiently within their organizations. When a problem is identified, professionals equipped with data analytics are capable of answering crucial questions such as:
• What was the cause of the problem? (Reports)
• Why did it happen? (Diagnosis)
• What will happen in the future? (Predictions)
• What is the best way forward? (Recommendations)
Data mining and analysis can help in answering these questions and boost the confidence on moving forward with the best approach. Data analytics is capable of improving any business process, whether it’s streamlining the communication in supply chain or improving the quality and relevance of offerings.
4. Improved Service Level Performance
When it comes to delivering the order in stringent timeline, it is quite critical to understand the viability of the option. Analytics can allow to predict the ability to meet customer demands, which are often for same day delivery, by understanding the average delivery times, nearest suppliers, the impact of any external factors i.e. traffic pattern, distance, etc. This analysis can allow to make and meet commitments, or pass on business where they know that delivery is not feasible, or to propose a next day delivery.
Predictable service can boost customer satisfaction and improve customer retentions.
5. Improved Supplier Management
Analyzing the customer feedback, complaints and refund requests can help in determining the suppliers’ performance, from on-time delivery, service or product quality perspective. Business can then take actions accordingly to manage their supply network in order to ensure that their clients are fully satisfied.
6. Maximize Customer Value
Past purchase data can help in identifying those customers, who are more likely to come back and do repeat business. It allows to optimize marketing investment, building long-term relationships with customers which then maximizes their value, and the level of repeat business.
7. Driving Down Costs
The sales data can reveal the trend in demand patterns, which may vary season-by-season. The data analysis can provide the flexibility of forecasting the upcoming demands, which can help in planning the inventory accordingly and optimizing down the inventory cost. Moreover, it can also improve staffing levels forecasts which can help to manage operational costs.
8. Improved Advertising
When it comes to effective advertising, sales pattern can show the effectiveness of different advertisement channels. Business can accordingly drive their advertisement expenditure on the right channels, in order to get the maximum sales.
In case of online advertisement, every advertisement is A/B and even C split-tested. All landing pages, pop-ups, and even product images are assessed for their effectiveness with tweaks being made to ensure maximum results. Even the positioning of products on the website is measured to identify the best location to help drive engagement and sales.
Advertising can be expensive, so it's important to know how to get the best return on the investment.
9. Better Product Management
Businesses can offer many different products, but it would be important to understand which would be the most saleable products or a combination of products and, this too can vary by region, and also seasonally. The data can be used to ensure that the business targets the right product at the right time, which helps to increase sales.