Far too many companies that I consult with sit on loads of good customer data and do nothing with it. It’s really amazing because in that data is a gold mine of insight.

An insight that can:

• Increase customer loyalty
• Unlock hidden profitability
• Reduce client churn

Are you resting on loads of data that you aren’t using? Would you like to read how you can use it? Here are the most popular ways of How DataMining Can Help You Get a Competitive Edge

Basket Analysis

Sometimes called “affinity analysis,” this seems at the items that a customer bought, which could help brick-and-mortar stores increase their layouts or online firms like Amazon recommend related products. The “basket” refers to what shoppers use when they are shopping.

It’s based on the assumption that you can predict future
customer behavior by past performance, including purchases and preferences. And
it’s not just grocery stores that can use this data.

Here are some steps it can be used in different industries:

• Assessing the use of credit cards. Typically, specialists mine credit card data to find patterns that might suggest cheating, but the data is also used to tailor cards around a variation of credit limits, terms, and interest rates and even collect a debt.

• Assessing patterns of telephone use. For example, you could discover clients who use all of the latest services and features your phone company offers to suggest they will need something new to stick around and then offer them an incentive to stay another year.

• Identifying fraud insurance claims. Through the mining of historical knowledge, insurance organizations can spot claims with a high percentage of recovering money lost through fraud and develop rules to help them flag future fraudulent claims.

And all the products don’t have to be acquired at the same time. Most client analytic tools can watch purchases over time, thus helping you spot trends or possibilities that you can test for future developments.

Sales Forecasting

This looks at when clients bought and tried to predict when
they will buy again. You could use this type of analysis to determine a policy
of planned obsolescence.

It is also looking at the number of clients in your market
and predicts how many will really buy. For instance, think if you have a coffee
shop in Seattle. Here are issues you might ask:

• How many people/households/businesses inside a mile of your store will purchase your coffee, and how many competitors are in that mile?
• How many people/households/businesses in 5 miles? And how many competitors in these 5 miles?

Database Marketing

By analyzing client purchasing patterns and looking at the
demographics and psychographics of clients to make profiles, you can create
products that will sell themselves.

Of course for a marketer to get any benefit out of a
database, it must continue to grow. You maintain database information from
sales, surveys, subscriptions, and applications. And then you target clients
based on this intelligence.

Database marketing starts with gathering information. For
instance, if you owner of a coffee shop, your database might consist of these
things:

• Buying records stored via a club card that you offer via incentives like 5% off purchases or collection of points.
• Contests you run to collect extra knowledge about where people live.
• Email newsletter you use to update clients weekly, but also to send out surveys in which you collect extra knowledge concerning new products and promotions.

As you gather data, start to look for opportunities like the best days to run a discount advertising. Ask yourself: Who are your local clients, and how you can turn these clients in advocates for your store?

Merchandise Planning

This is important for offline or online businesses. For the offline, a business looking to increase by adding stores can evaluate the amount of merchandise they will need by looking at the exact layout of a current store. For an online business, merchandise planning can help you manage stocking options and inventory warehousing.

Ignoring this database strategy can lead to bad performance
in times of customer service. If you can’t manage typical runs on services,
in-store expectations aren’t met, or your price doesn’t match the market;
clients will jump the boat and go to your competitors.

Card Marketing

If your company includes issuing credit cards, you can gather the information from usage, classify customer segments, and then based on information on these segments, develop programs that increase retention, boost acquisition, target products to develop and design prices.

There are costs built into issuing credit cards that most businesses can’t understand, but if you can…do it. Analyzing client purchasing patterns based on their credit card habits will give you insights into behavior that can lead to promotions and programs that will result in higher profits and better client loyalty.

Call Detail Record Analysis

If your business depends upon telecommunications, then you
can mine that incoming data to see use patterns, create client profiles from
these patterns, and then build a tiered pricing structure to maximize
advantage. Or you could build promotions that reflect your data.

A China mobile worker with about 700,000 clients wanted to
analyze their data to create offerings to fend off competition. The first thing
the project team behind gathering and analyzing the data did was to create an
index to describe caller behavior. That index then collected the callers into
15 segments based on elements like this:

• Minutes Of Usage per user on the average
• Local call rate
• Long-distance call rate
• IP call rate
• Roam rate
• Idle period local call rate
• Idle period long-distance call rate

From that data, the marketing agency then planned policies
directed at each segment, namely improving client satisfaction, delivering
quality SMS service for another group, and helping another group to use more
minutes.

Whether it’s based upon mobile user data or client service
calls, dive into the data available in call detail reports to look for ways to
increase current service, promotion opportunities, or ways to shorten time on
call.

Customer Loyalty

In a world where price wars occur, you will get clients jumping ship every time a competitor offers lower prices. You can use datamining services to help reduce this churn, especially with social media.

Market Segmentation

One of the best uses of datamining services is to segment your clients. And it’s much simple. From your data, you can break down your market into important segments like age, income, occupation, or gender. And this works whether you are running email marketing campaigns or SEO strategies.

Segmentation can also help you understand your competition.
This insight alone will help you know that the usual suspects are not the only
ones targeting the same client money as you are.

This is very important because when I ask most consumers who their competitors are, they give me a list of people. I then hand them back a bigger list. Most companies need to expand their circle of competitors out two or three times if they plan on competing efficiently. Datamining will help you do that.

Product Production

Datamining is also perfect for creating custom products designed for market segments. In fact, you can predict which features users may want, although really innovative products are not created by giving clients what they require.

Very truly innovative products are produced when you look at
the data from your clients and spot holes customers are demanding to be filled.
When it comes to building that product, these are the elements that must be
baked into the product.

• Fulfill an apparent need
• Offer something utterly different
• Set to enter the market with a different name
• Attractive design
• Serves a broad market
• Can be sold in generations
• Build an impulse-purchase price
• Cost to make is low enough to make a profit

Warranties

Lastly, datamining will allow you to predict how many people will really cash in on the warranty you’ve set up. This is also right for guarantees.

One of the best ways to building a successful guarantee is
to look at the data of past guarantees, sales, and earnings. Doing so may lead
you to offer a 110% money-back guarantee to get an edge over the competition.

Conclusion

The more data you gather from clients, the more value you can deliver to them. And the more value you can deliver to them, the more income you can generate. Datamining is what will help you do that.

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