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Companies to Research
Data Analytics
Resources: Customer/Marketing Analytics
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)
Descriptive Customer or Marketing Analytics
Descriptive customer or marketing analytics are a way of linking the customer or the market to the business through information or data, specifically the kinds of useful data the business will require to allow it to make effective actionable decisions. The focus of descriptive analytics is always on what happened (and why it happened), and on the behaviour of the customer or market.
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
Comprehensive Digital Marketing Strategy
Three kinds of digital media:
1. Owned Media (WEB PROPERTIES: website, mobile site, blog, social media channels)
2. Earned Media (SHARING: mentions, shares, reposts, reviews)
3. Paid Media (ADVERTISING: pay-per-click, display ads, retargeting, paid influencers, paid content promotion, social media ads)
Digital marketing strategy:
Leverage owned, earned and paid media for cross-fertilisation [Read more…] about Comprehensive Digital Marketing Strategy
MIS: Customer Data Collection
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]
Marketing Analytics (Focus On The Customer)
Marketing has changed. It’s no longer enough just to measure the campaign, how much it cost, how many sales were made, what profit or contribution was generated. Business has changed because the consumer has changed, and how (and why) the consumer engages with a business has changed too.
Of course, this has all been driven by technology, particularly the near-ubiquity of the internet. Businesses have had to learn to talk to their customers in different places and in different ways because of that. But it’s also meant that businesses have been able to gain a far greater insight into their customers (and others like them) than at any other time in the history of business. [Read more…] about Marketing Analytics (Focus On The Customer)
Designing Better Management Information Systems 2
Key Outcome:To give key users (management team) the information they need, when they need it, to make the best, most timely decisions so the company can achieve its strategic goals.
System Project Lifecycle:
Define – Design – Construct – Test – Train – Convert ( – Operate – Evaluate – Improve)
10 Stages: [Read more…] about Designing Better Management Information Systems 2