How You Can Identify Buying Preferences of Customers Using Data Mining Techniques

The New Gold Rush: Exploring the Untapped ‘Data Mining’ Reserves of Top 3 Industries

In a bid to reach new moms bang on time, Target knows when you’ll get pregnant. Microsoft knows Return on Investment (ROI) of each of its employee. Pandora knows what’s your current music mood. Amazing, isn’t it?

Call it the stereotype of mathematician nerds or Holy Grail of predictive analysts of modern day, Data Mining is the new gold rush for many industries.

Today, companies are mining data to predict exact actions of their prospective customers. That means, when a huge chunk of customer data is seen through a series of sophisticated, formatted and collective data mining process, it can help create future-ready content of marketing and buying messages, diminishing scope of errors and maximizing customer loyalty.

Also a progressive team of coders and statisticians help push the envelope as far as the marketing and business tactics are concerned by collecting data and mining practices that are empowering.

Mentioned below is a detailed low-down of three such industries (real estate, retail and automobile) where LoginWorks Software has employed the most talented predictive analysts and comprehensive behavioral marketing platforms in the industry. Let’s take a look.

Real Estate Industry Looks Past the Spray-And-Pray Marketing Tactic By Mining User Data.

A supremely competitive market that is to an extent unstructured too, the real estate industry needs to reap the advantageous benefits of data mining. And, we at LoginWorks Softwares understand this extremely well!

Our robust team of knowledge-driven analysts make sure that we predict future trends, process the old data and rank the areas using actionable predictive analytics techniques. By applying a long-term strategy to analyze the trend and to get hold of the influential factors that are invested in buying a property, our data warehouses excels in using classical techniques, such as Neural Network, C&R Tree, linear regression, Multilayer Perception Model and SPSS in order to uncover the hidden knowledge.

By using Big Data as the bedrock of our Predictive Marketing Platform, we help you zero-in on the best possible property available for your interest. Data from more than a dozen of reliable national and international resources to give you the most accurate and up-to-the minute data. Right from extracting a refined database of one’s neighbourhood insights to classic knowledge discovery of meaningful l techniques, our statisticians have proven accuracy. We scientifically predict your data by:

•    Understanding powerful insights that lead to property-buying decisions.
•    Studying properties and ranking them city-wise, based on their predictability of getting sold in the future.
•    Measuring trends at micro level by making use of Home Price Index, Market Strength Indicator, Automated Valuation Model and Investment analytics.

Our marketing platform consists of the mentioned below automated features:

Data Mining Techniques for Customer Relationship Management and Customer Retention in Retail Industry

Data mining to a retailer is what mining gold to a goldsmith would be! Priceless, to say the least. To understand the dynamics and suggestive patterns of customer habits, a retailer is always scouting for information to up his sales and generate future leads from existing and prospective consumers. Hence, sourcing your birth date information from your social media profiles to zooming upon your customer’s buying behaviour in different seasons.

For a retailer, data mining helps the customer information to transform a point of sale into a detailed understanding of (1) Customer Identification; (2) Customer Attraction; (3) Customer Retention; and (4) Customer Development. A retailer can score potential benefits by calculating Return on Investment (ROI) of its customers by:

•    Gaining customer loyalty and long-term association
•    Saving up on huge spend on non-targeted advertising and marketing costs
•    Accessing customer information, which leads to directly targeting the profitable customers
•    Extending product life cycle
•    Uncovering predictable buying patterns that leads to a decrease in spoilage, distribution costs and holding costs

Our specialised marketing team targets customers for retention by applying myriad levels of data mining techniques, in both technological and statistical perspective. We primarily make use of ‘basket’ analysis technique that unearths links between two distinct products and ‘visual’ mining techniques that helps in discovering the power of instant visual association and buying.

Role of Data Mining in Retail Sector

Spinning the Magic Wheel of Data Mining Algorithms in Automobile Industry of Today

Often called as the ‘industries of industries’. the automobile industry of today is robustly engrossed in constructing new plants, and extracting more production levels from existing plants. Like food manufacturing and drug companies, today, automakers are in an urgent need to build sophisticated data extraction processes to keep themselves all equipped for exuberantly expensive and reputation-damaging incidents. If a data analytics by Teradata Corp, a data analytics company, is to be believed then the “auto industry spends $45 billion to $50 billion a year on recalls and warranty claim”. A number potentially damaging for the automobile industry at-large, we reckon!

Hence, it becomes all the more imperative for an automobile company of repute to make use of enhanced methodology of data mining algorithms.

Our analysts would help you to spot insightful patterns, trends, rules, and relationships from scores and scores of information, which is otherwise next to impossible for the human eye to trace or process. Our avant-garde technicians understand that an automative manufacturing industry does not interact on one-to-one basis with the end consumers on a direct basis, hence we step into the picture and use our fully-integrated data mining feature to help you with the:

•    Supply chain procedure (pre-sales and post-sales services, inventory, orders, production plan).
•    Full A-Zee marketing facts and figures(dealers, business centers, social media handling, direct marketing tactics, etc).
•    Manufacturing detailing (car configurations/packages/options codes and description).
•    Customers’ inclination information (websites web-activities).

Impact of Big Data Analytics of Direct Vehicle Pricing

Bottom line

To wrap it all up, it is imperative to understand that the customer data is just as crucial for an actionable insights as your regular listings data. Behavioural data and predictive analysis is where the real deal lies, because at the end of the day it is all about targeting the right audience with the right context!

Move forward in your industry by availing LOGNWORKS SOFTWARES’ comprehensive, integrated, strategic and sophisticated Data Mining Services.

Source: http://www.loginworks.com/blogs/web-scraping-blogs/can-identify-buying-preferences-customers-using-data-mining-techniques/

Get Yourself Out Of A Scrape With Free Online Translation Tools

Most people who have been abroad or who at some stage have studied other languages tend to think of themselves as fair linguists. Granted, whilst abroad, they may very well be able to order lunch and refreshments and converse on a basic level, however, when faced with written documentation, they very often find their ability somewhat lacking.

The problem is that when speaking to someone in person, very often the context of the conversation with possibly a few accompanying hand gestures, generally overrides any deficiencies in vocabulary or grammar. When you actually see a language written grammatically though, simple conjugations often change recognised verbs, into something quite alien.

Faced then, with (usually important) documents from abroad, most people find themselves in a bit of a fix.

Luckily, the answer is easily within reach - you can easily access free translations online.

A cursory scan of any of the major search engines on the internet will come up with a great many free online translation sites. They are all very easy to use and it's really just a matter of typing in the desired word or phrase, selecting the source language and the target language and then pressing a button.

These free online translation tools, can be a real boon. They will literally translate whatever you put into them and can certainly give you a basic understanding of what a foreign document is trying to relate.

What they won't do, however, is give you a clear and precise translation because they literally translate word for word, the result will not be grammatical and will not necessarily make sense without having to piece together the text and frame it in the context of the subject matter.

Following the link above, however, will take you to a compilation of the best free translation resources. There is good reason to visit a site with a variety of translation engines. Every engine is slightly different and by having the use of more than one resource, you will be able to easily cross-check any words or phrases that don't quite come out sensibly. It's always good to have a fall back and It might just get you out of a real scrape.

One word of advice though: if the translations that you need to undertake are at all important to your company's business, or a mistranslation could have serious ramifications on your business were they to be at fault. You should always engage a professional translation company. Ultimately, there is nothing like a human translator to make perfect sense out of a linguistic muddle!

Source: http://ezinearticles.com/?Get-Yourself-Out-Of-A-Scrape-With-Free-Online-Translation-Tools&id=706676

What is Blog Content Scraping?

Blog content scraping is an act usually performed with scripts that extract content from numerous sources and pulls it into one site. It is so easy now that anyone can install a WordPress site, put a free or commercial theme, and install a few plugins that will go and scrape content from selected blogs, so it can be published on their site.

Why are they Stealing my Content?

Some of our users have asked us why are they stealing my content? The simple answer is because you are AWESOME. The truth is that these content scrapers have ulterior motives. Below are just few reasons why someone would scrape your content:

•    Affiliate commission – There are some dirty affiliate marketers out there that just wants to exploit the system to make few extra bucks. They will use your content and other’s content to bring traffic to their site through search engine. These sites are usually targeted towards a specific niche, so they have related products that they are promoting.

•    Lead Generation – Often we see lawyers and realtors doing this. They want to seem like industry leaders in their small communities. They do not have the bandwidth to produce quality content, so they go out and scrape content from other sources. Sometimes, they are not even aware of this because they are paying some scumbag $30/month to add content and help them get better SEO. We have encountered quite a few of these in the past.

•    Advertising Revenue – Some folks just want to create a “hub” of knowledge. A one-stop-shop for users in a specific niche. If I had a penny for every time someone has done this with our content, then we would have a few hundred pennies. Often we notice that our site content is being scraped. The scraper always replies, I was doing this for the good of the community. Except the site is plastered with ads.

These are just a few reasons why someone would steal your content.

Source:http://www.wpbeginner.com/beginners-guide/beginners-guide-to-preventing-blog-content-scraping-in-wordpress/

Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

Basic process of CRM data mining includes:

1. Define business goal
2. Construct marketing database
3. Analyze data
4. Visualize a model
5. Explore model
6. Set up model & start monitoring

Let me explain last three steps in detail.

Visualize a Model:

Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:

Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:

To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.

For any queries related to Data mining CRM applications, please feel free to contact us. We would be pleased to answer each of your queries in detail.

Source:http://ezinearticles.com/?Customer-Relationship-Management-%28CRM%29-Using-Data-Mining-Services&id=4641198