To the Stars
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
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 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)
A word before I begin
You can do no better in learning Python programming for data handling/analysis than to study for yourself one of Charles Servance’s MOOC’s, or to download and work through his freely-available, ‘remixed’ open-source book (see References below for links to both). I am not even standing of the shoulders of giants here… I am merely scurrying along way behind them all, picking up what few crumbs of knowledge and wisdom I can along the way. Blogging my own educational journey – as a 40-somthing woman heading into the world of tech – is a way to help me consolidate my own learnings. If it can help you too – above all by showing empirically that “if she can, then I can” – it will have served a double purpose. [Read more…] about Coding 101
An Update on Where I’m At Mentally/Emotionally:
Returning to the Data Science stream of my Personal Training Plan, I need to get set up with various tools and online accounts so I can start to go deeper into my studies. As I mentioned when I started this stream, my initial thoughts were of trepidation at signing up and entering into this new world – I felt intimidated by it all. So much so that I did a quick 90 degree detour into Business Analytics where I feel much more comfortable, being on familiar ground.
But I’m also reminded of how motivated I feel to change my career trajectory, and my confidence that this is possible to do, even now in my late 40’s. And I’ve been given some great opportunities by the company I work at to move in a more systems-and data-oriented direction. I feel very lucky about that. So I’m grabbing that opportunity with both hands. Coupled with my self-led learning (which is, of course, heavily supported by various MOOC’s provided by so many excellent educational institutions) I am sure I can make this work out in the best possible way for me. [Read more…] about Tools for Data Science
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
Leverage Risk Metrics
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