There are too many businesses today that are sitting on gold mines, namely their customer data. Customer data can provide tons of useful insights that can enable a business to:
- Build customer loyalty
- Unlock hidden avenues for profitability
- Reduce client agitation
If youve been sitting on your customer data, here are five practical ways you can use it to build value for your business.
1. Basket / Affinity Analysis
This technique analyzes products/services bought by a customer, which can then be applied to improve product layouts in brick-and-mortar stores, or related product recommendations for online retail outlets. The basket refers to the collection of items selected by one consumer during their shopping expedition.
The technique assumes that future customer behavior can be predicted through past performers, i.e. their preferences and purchases. This can be applied by more than just retail stores, such as:
- Online e-commerce stores can evaluate credit card data to find patterns that can highlight fraud incidents, as well as tailor reward cards with optimal limits, interest rates and terms for consumers
- Telephone use identify which customer segments respond to telephone calls to action on websites and identity reasons why this is the case, and how the CTAs can be improved to get more people calling the business.
This product information doesnt have to apply to single purchases analytics tools can be used to track each customers buying habits and preferences over long periods, enabling you to draw patterns and predictions that you can use when promoting products and services in future.
2. Sales Forecasting
The aim of this technique is to look at when customers buy certain products, and when they are likely to buy again. The strategy can then be used for inventory management or planned obsolescence strategy. In the same vein, you can identify how many customers buy which products within your online store and how many dont and how you can target them to get them to become your customers.
Local based businesses with an online presence can apply this technique for both their online audience and local audience by determining how the audiences can be effectively reached and drawn to the shop. This helps with capital management and planning, in realistic, optimistic and pessimistic cash flow prediction scenarios.
3. Database Marketing
The idea behind this technique is to create product groups that can sell themselves. This is done by careful analysis of customer demographics, psychographics and buying habits. Databases of customer information can be very valuable for your online and offline marketing teams, but these databases must be constantly updated to ensure they reflect the latest state of the market.
As a result, the database will be fed with data from different sources including surveys and questionnaires, subscriptions, sales and website analytical metrics among creating a pool of intelligence with which customers can be effectively targeted. Collection of information is the most important part of database marketing; the information may then be used when deciding which direction current and future online marketing strategies should take.
4. Inventory Planning
Inventory management is important for any company that sells products and/or consumable services. Inventory planning can help online businesses maximize value from their inventory warehousing decisions and stocking options.
Using data mining and analytical techniques, you can anticipate, prevent and/or effectively deal with the following inventory dilemmas.
- Old stock this can be reduced by accurately knowing the demand for each of the online stores products and stocking up appropriately. In addition, promotions and discounts can be pre-planned to get rid of old stock while it can still fetch some profit.
- Product selection studying your databases can help you determine what your customers want, and you can do away with non-sellers. This includes collecting information on competitors merchandise.
- Stock balancing there are downsides to having either too much or too little stock. Customer purchase data can however highlight the right quantities to stock for different buying seasons.
- Pricing discover customer sensitivity to pricing by analyzing yours and your competitors sales changes with respect to price margins, then adjust your prices accordingly.
Without effective inventory planning and management, you are likely to end up with stock-outs, causing you to lose clientele to your competitors and poor returns from overstocking non-selling products. You need to know what the market wants at each time, and at each period, and data mining can help with that.
5. Customer Loyalty
This is especially important for elastic markets, where a small price change can cause customers to jump ship to competitors offering lower prices. By knowing how price changes affect customers buying habits, you can mount a social media campaign to minimize the churn of customers in the face of slightly lower prices by another competitor.
By meaningfully attracting and engaging with your consumers, you will build a sense of relationship with the brand, so that customers will not simply bow out in the face of a few shillings price difference given by a new competitor in the market. A few programs that can be implemented include:
- Employee engagement ask your employees, who are the first contact point with customers, to give ideas on how customer engagement can be improved based on their own consumer interactions, including product selection and development questions as well as future growth opportunities
- Facebook use data from your customer clusters on Facebook to determine the needs of various clusters and come up with ways to address their engagement needs
You can focus on creation of value for customers, which is what will attract customers to stay in the face of price wars. Knowing why customers leave is pivotal to knowing how to keep them from doing so.
Conclusion
As you collect and use more data from your customers, you will know how to deliver relevance and value to them, and in doing so, generate more revenue for your business. Data mining is essential to all levels of business, and the entire process from customer acquisition service delivery to relationship building. You will definitely be smiling all the way to the bank at the end of it all.
