Marketing Strategy: Retail, Banking
Mar/092
Financial Institutions offer various products to its customers such as personal loans, home loans, savings account, credit cards and so on..
It is very essential for a financial company to know, which user to target for what product and when. The goal of data analytics and data mining department is to arrive at accurate answers to these 3 questions, (Which User, What Product, When), trust me it is a rewarding exercise for the bank, users and definitely the analytics manager.
The problem is very simple. A customer may have purchased a single product or multiple products from a bank. The company would ideally like if all its customers bought all of its products. This possibility however does not exist, therefore without any targeting model; the company would be wasting money, time and resources by randomly targeting customers for its products.
Using a little sophistication of data mining techniques, we would be able to build a targeting model or a response model on customer base. A response model is a predictive model which estimates the future behavior of a given customer even before it occurs. Even with a fair amount of accuracy it can be very useful for company in saving majority of costs in various departments/channels. There are various types of data available for analysis like demographic, behavioral, psychographic / attitudinal. The above data can be very useful in data mining methods, however the cost, usefulness and expertise to store / retrieve data has to be assessed and judged.
Giving an example: A customer has savings account in a bank, based on the information given to the bank along with account status and history, we could target her as a prospect for a personal loan product based on a logic / algorithm.
The logic / algorithm could be as simple as if a customer from metro with account balance of Rs 1,00,000 or more for over 6 months should be a prospect for home loans Rs 20,00,000 or personal loans over Rs 3,00,000. This is a simple example; however it could be a complicated neural network or logistic regression model.
Cross Sell Models: A customer of a product A, is a likely prospect for product B if his account activity positively predicts likelihood of purchase. Target model has to predict purchase of product B.
Up Sell Models: A customer can be targeted for higher segment product in the same category based on his account status and demographics. Normal saving accounts customers can be sold for Premium segments customers, if his account balance is over a period of time.
Deep Sell Models: A customer can be sold more of same product based on his need. Target model has to predict his need.
These target models are also called response models that only predict the purchase behavior of a customer for a given product. This model is ineffective as the cost of randomly targeting a customer for product is LESS THAN cost of targeting using predictive response model.
The main reason is because of below limitations of traditional response model
A) All customers behave in two ways: Purchase or DO NOT Purchase
B) Behavior of customers during absence of any marketing activity.
C) Maximum lifetime value to be derived from customer is unkown, this will result in underselling or selling lower value products when higher products could have been sold.
IF these issues are taken care of by strong statistical modeling then loss making response model can be made profitable.
The original article was found on http://www.praveenkodur.com/, Copy rights are reserved.
Disclaimer: These are my personal views and not a view of any organization or body.
Internet Banking Web Analytics
Mar/092
Internet Banking is a different arena of web analytics, which require a totally different perspective and problem solving capabilities. The rest of the article will talk about some problems and solutions in such areas.
In traditional ecommerce sites, KPIs and key metrics are tracked by setting up page-tracking and Goals. Users are tracked through funnel process, like movement from one page to another page until the sales confirmation page. Usability and productivity of the page is evaluated by bounce rate, exit rate, conversion rate and click stream behavior on each of these pages.
However, consider a case of Internet Banking, it is very interesting that such funnel navigation or bounce rate gives a very little information about its effectiveness, here is why? Lets say a user has a bank account and is using Internet Banking for transaction.
There are various things are tracked to understand his behavior, a person who wants to transfer funds from one account to another will do it even if it is a difficult process and does not fully understand, a user will try and figure out the ways to understand process and transfer funds online. Therefore the drop out rate in funnel navigation is very less, unlike ecommerce sites. Most users will inevitable complete the funnel and navigate all important pages to reach thank you page, even if they do face difficulties. They would invariably figure out how to do a transaction online.
The problem for web analytics guy is, a lot of users seem to be using internet banking very well but how do you find out where exactly is the problem, what needs to be mended.
Here are some areas of data to be looked into, that gives us insights in this direction.
1) Pageviews of Error pages.
a. How many times error pages were thrown up?
b. Source of error pages, which page led to error pages most and their ranking.
c. Errors per transaction.
2) Pageviews of help section and FAQs, which part of help section was most viewed and their ranking.
3) Total Pageviews per page per transaction. Example, a fund transfer has 4 pages, how many times each of the pages were viewed per transaction.
4) Offline feedback on errors and complaints on Internet banking transaction.
5) Average time taken per page online
a. Rank pages on average time per transaction
6) Number of fraudulent transactions or security complaints.
These are my personal views and opinion on this subject. Please do let me know your views as comments.
This article is originally found on http://www.praveenkodur.com/ Copy right reserved on http://www.praveenkodur.com/
Google Adwords Management Made Easy
Aug/0818
There are Internet companies both in US and India which have resources to manage PPC accounts more than the number of PPC accounts itself.
If a company has 1 million keywords in PPC account and is managed by 5 people then 2 Lakh keywords are managed per person!!.
This is a wrong strategy for growth. Google is spending billions of dollars to make life easier for advertiser, they are launching new features & tools regularly which gives more insights into the PPC accounts. There are lots of other companies which have launched various products around PPC management such as Betterppc’s Ad optimization, KeywordSpy, Compete Search Analytics, Shoemoney Tools and many more.
These tools along with the Google tools can greatly help reduce the PPC management process, time, and effort, increasing efficiency. Bigger accounts do not need as many people to manage. One single person can do the job of 20 people effectively, if the tools are used effectively.
PPC Management is like looking at stock market. A good investor is always looking at price of the stocks he has invested or stocker broker is looking at price of the all companies on regular basis. The difference is that in PPC you are spending money every day, while in stock you just buy once.
There are software’s available for keyword research, duplicate keyword identification, Keyword structuring many more.
With advance skills in Microsoft Excel along with the help of these tools can make life a lot simpler and easy with less work and less resources.
Google has launched Ad planer, upgraded the Google keyword tool by displaying numbers instead of relative graphs. The amount of time required to create a media plan or to come up with right set of keywords for PPC campaigns has been greatly reduced. Additionally Google has create a campaign library which contains a list of template which can be used to reproduce campaigns of the given order.
The ammunition and tools which Google offers now and in future will help make PPC Management easy, effective and less time consuming.
PPC managment requires daily changes to bids and/or keywords. But the point is let Google worry about making things easy for you in terms of managing PPC campaigns.
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Measuring ROI through Analytics
Jun/0824
An Internet or web enabled business thrives on the user base who have access to internet, of which who are active online.
The idea of this blog posts and future blog posts is to identify problems in web based business and how analytics can help solve it?
Blogging and Blogs
You have a small blog and spend considerable amount of time updating it, also have spent some money in creating and putting it up live. Measuring the success of a blog is not just pageviews, subscribers and unique visitors count.
ROI of a popular blog can be huge, if you have rich content and have active RSS subscribers. You don’t need a resume. Every popular blogger gets job offers regularly flowing into his email. Above this you have created a brand for yourself. This is a huge economical benefit considering the money and time you spend on make your blog active. If you have a great blog then you have separate brand and identity for yourself.
Small Scale Business Online
Concentrating on search engine marketing, seo, affiliate marketing to generate profitable visitors to site is fruitful. This is the cheapest form of advertising online. You have control over spends and will be able to monitor your ROI. Set up Google Analytics or any other analytics tool which will help you look at the visitor information.
Conversion University from google is very helpful in optimizing the website for higher conversions and sales (http://www.google.com/support/conversionuniversity/bin/answer.py?answer=77123)
Small scale business must focus their marketing efforts cleverly around geo-locations to get maximum return from marketing & advertising. The site must clearly offer maximum benefit & response to their end users as promised in their USP. Most sites initially work on small set of customer base and keep them satisfied at all circumstances.
These companies are ecommerce sites, shopping sites, travel agent sites that are looking to sell products to their websites’ visitors. They should target at long term steady and consistent growth not looking to achieve instant traffic hoping to dramatically increase page-views and visitor count hoping make revenue quickly and grow faster.
Large Businesses Online
There are various large online website who advertise heavily online & offline for the purpose of promotion. The spend a big amount of money with an objective to increase visitors, page views hoping to increase brand value. It is unwise to spend money on marketing, advertising without looking at the actual value it adds to their users (customers).
Increase in page views and visitors may not proportionally be related to increase in revenue and profit. There are definitely smarter ways to reduce cost of marketing & advertising without impacting the bottomline.
I read about many large advertisers in US & worldwide who have decreased spends on search marketing as it has become unprofitable after a certain limit. They have found search engine optimization, social media marketing ways more effective to gain relevant traffic to their websites for increasing their sales.
Measuring ROI through every channel and making them profitable is very essential and must be the key factor
EXAMPLE:
The traffic to my blog has constant traffic from social media sites like stumbleupon and other social network sites. Few days it has huge spikes of about 2000 hits in a day from stumbleupon alone, totally free traffic.
Blog attracts about 16% of overall traffic from social media sites of which 48% contribution is from Stumbleupon alone.
The cost of promotion on stumbleupon is consuming few hours of time in writing rich useful content and building a network of bloggers, friends & general users. Comparing this with search marketing campaigns, same amount of traffic might have costed me few thousand dollars.
Never be afraid to use new format of media, content for promotions such as Videos, Apps, Images, podcast, audio files, flash files etc. It is just a new form of content by the underlining principle of promotion remains the same.
Reading:
Measuring ROI from SEO : http://searchenginewatch.com/showPage.html?page=3625973
Measuring ROI from Social Media Marketing: http://www.pronetadvertising.com/articles/measuring-the-roi-from-social-media-marketing.html
This Article is originally found on http://www.praveenkodur.com/blog/