Best of the retail marketing web - August 2015
Here's a curated collection of recent blog articles that we think are interesting to a retail marketer.
Gaining traction as a new e-commerce retailer...
If you're an e-commerce newbie then you might want to read this article from the guys at Leapfrogg. Their panel of premium consumers discuss the concerns they have shopping with a new online brand. Payment security, customer service with respect to issue handling and flexibility around returns are all concerns that create barriers for new brands. Exclusive products and offers have the ability to attract consumers to new brands. Find out more below
The power of prediction in customer retention
Retention should be a bigger priority for most retailers who sell products which are susceptible for repeat purchases. This article provides some compelling evidence for why a focus on keeping hold of customers through predictive analytics can pay dividends. Here's a quote directly from the article:
"Those brands that have applied predictive modelling to personalisation have seen as much as 95% of revenue coming from just 5% of customers. Not only are these companies improving the likelihood of individual customers remaining loyal to a brand and not falling prey to a competitor’s acquisition tactics, but they are significantly increasing customer lifetime value for every individual."
The argument for automation
We bang on about marketing automation quite a lot! There are loads of marketing campaigns you can automate for. This article, although somewhat biased to B2B companies reflects a compelling argument why automation is a good thing (thought we don't like Amazon as an example. If you want to know why, then get in touch!). Effective Marketing Automation is harder to execute in a B2C retail business, but certainly achievable, especially when it comes to customer lifecycle marketing.
Data capture strategy - don't nod off, this is important stuff!
Why like the way this article sets out how your business/marketing objectives should drive what data you capture and use. Starting with the objective and working backwards from there is an efficient approach. Starting with a load of data and seeing what might be interesting is not. When it comes to specific points on data capture we totally agree with the reference to free text to avoid anomalies.