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Digital Marketing (Web) Metrics
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To the Stars
By debkr
By debkr
Articles
Knowledge@Wharton (Wharton Business School):
Are Your Customers ‘Clumpy’? What Binge-buying Means for Marketers
Predicting — and Monetizing — the Lifespan of a Tweet
Forbes:
Article and podcast on Customer Centricity
Academic Papers
Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data
Videos
Knowledge@Wharton video: Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data
Predictive Models
In Excel: http://brucehardie.com/notes/010/
R Package: https://cran.r-project.org/web/packages/BTYD/index.html (BYTD = Buy ‘Til You Die)
By debkr
There are three kinds of descriptive analytics, each being used in a different kind of situation, or where the kind of decision management wishes to make varies. [Read more…] about Descriptive Customer or Marketing Analytics
By debkr
Active data collection: e.g. surveys
Passive data collection: e.g. transactional data – across all touch-points/all channels (single customer view)
Data quality/usefulness: complete, accurate, timely, allows for managerial decision-making
Data for decision-making (increasing sales):
(Point of sales data: what are they buying, where/how are they buying, what triggered the purchase, what do they have in their basket, etc.)
1. Impact of promotions (both short-term and long-term): who buys our products on promotions; how many of our customers are cherry-pickers; will cherry-pickers become loyal (& if so, how); are today’s promotions cannibalising future promotions/sales
2. Impact of display (retail, catalogue, online): which types of display work best to optimise sales
3. Sales within and across categories: which products (or categories) are substitutes; which products (or categories) are complements; which products are working well together and which are cannibalising each other
4. Impact of pricing: standard list price, discounted price, membership discounts/launch discounts, currency pricing overseas
5. Effectiveness of new customer recruitment: how did first time buyers find us; how much did they purchase; which products or offers will optimise their purchases
Data for decision-making (improving profitability):
[TBC]
Data for decision-making (reducing risk):
[TBC]
By debkr
System Project Lifecycle:
Define – Design – Construct – Test – Train – Convert ( – Operate – Evaluate – Improve)
10 Stages: [Read more…] about Designing Better Management Information Systems 2
By debkr
The greatest risk to a company’s ability to survive is when it owes money to creditors or lenders. Here, its ability to pay back those creditors must be viewed as a critical metric for the company to monitor, particularly given various uncertainties the company may face in the current economic climate. Clearly a business which is cash-rich and carries no debt is in a much happier and healthier (less risky) situation, although even here it should still monitor its cash inflows and outflows and carefully manage its working capital cycle. But a company which owes money to others – especially when it is also waiting on receipts due from its own debtors/customers is in a far riskier position. [Read more…] about Risk Metrics 2
By debkr
Inventory Metrics
Generally in traditional manufacturing or retail businesses, the largest percentage of costs relative to sales is taken up by costs of the goods being sold. Before selling, the goods will be sitting on the company’s Balance Sheet as Inventory (which will usually be valued at the cost paid to make or buy that product) and likewise the physical product itself will be sitting around either on a shelf in a shop, in a factory or held in a warehouse or distribution centre. [Read more…] about Profitability Metrics 2