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How Can Data Mining Help in Getting More Customers?

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July 28, 2022

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Data depict fact. Even, you can have more customers if you figure out their intent, which is inside their web journey and brand experience. There are limitless leverages that businesses or entrepreneurs can have through niche-based records. What they actually do is mining, which is the base of any intelligence. To fuel this process, you need databases. Because of this reason, the global alternative data market size is projected to be worth $143.31 billion by 2030 according to Grand View Research. This figure is likely to show a staggering spike from $2.7 billion in 2021, which is forecasted to scale at a compound annual growth rate of 54.4% till 2030.

Vast Range of Data Sources

The decision-making mechanism is ever-evolving by integrating a ton of new types and sources of alternative data. These alternative records are called from wide-ranging and disparate sources, like financial records, satellites, sensors, IoT-enabled products, e-commerce sites, public records, mobile devices, social media, web traffic, and more. All of these sources let you scrape pieces of information, which has become, by far, the most common method of procuring datasets.

All in all, this collection is meant for discovering the intent of customers. It can let you figure out what to recommend for converting them from customers to actual buyers. You can get the way to make it truly happen through data mining and analysis. Both terms are interconnected & significant.

Where data mining discloses the “correlation” among different sets of records, data analytics translates insights into decisions and predictions for improving practice. There are several ways to reach any decision via these two processes in no time.

Let’s have a roundup of methods that can help in digging insights.

1. Market Basket Analysis

It’s no less than a shopping experience from the supermarket. You can identify customer buying habits & discover complementary items that are associated with their shopping carts. Moreover, data can let you gain insight into frequent buys by customers. This finding can help retailers, wholesalers, and distributors to develop feasible marketing strategies for drawing decisions.

The most common use of this analysis can be understood through the mining of these details:

• Cost monitoring
• Filtering fraud insurance claims
• Measuring the use of credit cards
• Understanding the pattern of telephone use

These insights can let you observe customers’ purchases over time, ensuring opportunities for future promotions.

2. Sales Projection

A customer’s buying journey and CRM data can let you predict when he will buy again. With the mining method, you can determine the consistency of that purchase. The purchase would be crystal clear, which guide you to figure out complementary and supplementary products for selling.

Look at the purchase history of all customers in your market and foresee how many are likely to buy. The answer to these queries can also make your planning more feasible:

• How many buyers invested in a particular product?
• How many competitors do you have in that niche?
• How many are above you in online searchability?
• At what price they are selling the same products as you do?

This is how you can categorize projection into realistic, optimistic, and pessimistic. It would let you find out how much capital you should have to bear the surplus demand or the situation when don’t go as you thought.

3. Merchandising Strategy

The merchandising strategy can help you understand the ultimate objective that you are likely to achieve for your business’s success and how to measure its success rate. It is indeed helpful for offline and online businesses.

Offline businesses can scale up, evaluating the volume or amount of merchandise that is needed. It can be predicted by measuring the exact draft of the current business operations.

Online businesses can also prepare merchandise planning to estimate inventory and its warehousing.

Focus on these points to make it effective for online and offline merchandising planning:

• Maintain current and updated digital records or a PDF white paper of stock
• Draw customer insights for mining their intent patterns, while including competitor intelligence.
• Mine your inventory or stock data throughout the year, especially during seasons when the demand is at its peak.
• Transaction database mining can let you draw and decide the ideal price for selling your products in accordance with customer sensitivity.

Avoiding this strategy can let you generate the least revenue because you won’t be able to balance out demand and supply, which certainly ends up in a shortage or surplus of products. This loss would be your competitors’ gain, as customers will leap to your competitors for the products.

4. Call Records Mining

The contact list of your current customers and prospects enriches you with many opportunities to mine and convert. With call mining, you can draw patterns of the calls showing the most and the least interest. Build profiles accordingly and then, work on price structuring to maximize conversion rate.  This tactic can also enable you to strategize promotions corresponding to the analysis of those patterns.

These details can let you understand and segment the interested and the least interested customers:

• IP call
• Remote call
• Call on Roaming
• Location-based calls
• Average minutes per user call

These details can let you decide how to improve customer experience, where the quality lapses, how to maximize conversion on a short call, and how to encourage marketing strategies.

5. Leverage on Warranties & Guaranty Data

Exploring customers’ brand experience can let you understand how many customers intended to cash warranties and guarantees.

This exposure will introduce you to the tips for improving sales. For this purpose, get deep into the cases of warranties and guarantees and try to understand the reasons for returning the product.

You can get through:

• Net sales
• Profit
• Settlement data under guarantee schemes

These details will segregate buyers under guarantee and warranty seekers. Then, you may start balancing both plus and minus without damaging the customer experience.

Summary

The business requires data mining to predict and settle down challenges by using data-driven intelligence. Call records, merchandising strategy, guarantee, and warranty data, and sales and marketing basket analysis can help in skillfully analyzing for profitability & scalability.