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.

Distribution network strategy using GIS

Setting up a physical distribution network is a strategic and resource intensive decision. One of the key success mantras for large corporations has been "Being present at right place at the right time". This was achieved largely through an optimal channel strategy which maximized the RoI on every dollar spent towards setting up the distribution network.

But what happens if it is not optimal! Obviously, you miss out on key target customers if you are not able to reach them out. Moreover, if you are present at wrong places, you are not able to recover the cost of setting up the channel; this could carry huge monetary implications for businesses with large stores e.g. automotive showrooms, hypermarkets, etc. There are many other implications of setting up a shop at wrong place viz. mismatch with desired brand positioning, operational inefficiency, reduced customer experience, etc.

So, how to plan the most optimal network strategy? Though, the specifics of answer to this core question would vary from business to business and across geographies, however, there are a few common guidelines that can help business in general. These guidelines have been devised basis the previous research work that was carried out for a large business conglomerate with multiple business lines. The research was a mix of Secondary research, Primary qualitative & quantitative research, and GIS mapping. The primary research was conducted with an objective to understand consumer expectations and drawing the catchment areas for existing distribution points. GIS was used to map all the key locations in the country including Client's distribution points, Competition's distribution points, Malls, Public transport points, Upcoming projects, Major new developments, etc.

Based on findings of the research, the top 3 guidelines are summarized below:

1. Identify the emerging geographical clusters
With rise in urbanization (esp. in developing countries), the cities are expanding rapidly. The areas that were considered to be outskirts at few years back are now very well the center of these cities. Thus, new markets are emerging in these growth hubs and existing channel might not suffice. If setting up a new shop / distribution point involves significant investment, it is critical that such growth hubs are identified well in advance so the investment is appropriately made and the shop is ready by the time population growth reaches critical mass. This is bound to offer a great first-mover advantage to brands that are already established both in terms of cost of investment and brand visibility.

2. Map your competition
Consumers like to compare offerings from multiple sellers and prefer to do so at a common place. Traditionally, consumers fulfilled this need by visiting 'bazaars' (local markets) and now the digital consumers do it so by hooking up to online marketplaces. Thus, the importance of being among peers cannot be understated if you want to get into consideration set of buyers. Thus, if you are an automotive showroom, ensure that you are present in a geographical cluster where other brands (of your competitive spectrum) are present

3. Identify the hot spots
Even though, marketers feel that they have wide channel coverage that should be adequate for market reach, it is essential to understand the same through consumer lens. When consumers look for a product, it is seldom in isolation. The consumers would prefer to spend their time and energy in reaching out those channels which can provide them maximum value. This value could be in terms of meeting multiple needs, overall cost of reaching there (time + money + hassle). Thus, marketers need to look beyond their immediate competition and try to add value to consumers. For example, an automotive service center needs a larger ecosystem of other entities in its vicinity to be popular. Consumers would want to meet their complete need of a car repair including spare parts shop, tires shop, batteries, mechanics, etc. Thus, it is essential to identify the hot spots where the competition is underrepresented but there is market opportunity based on overall ecosystem.

These generic guidelines need to be part of every discussion, document and decision of the network expansion plan. At higher level, they might sound extremely obvious, but it is easy to miss them out when actual decision on a new geographical location is made. Other real estate related considerations become key drivers and larger strategic goals take a backseat!