Predictive analytics a lazy mans way to riches! - SwiftERM

Predictive analytics is a lazy man’s way to riches. If you’re killing yourself putting the hours in, with little reward, why not search for an easier way? Who says that in order to succeed you have to flog yourself to death? How about a trying a system which identifies each one of your consumer’s next most imminent purchase, then populates an email in order or greatest likelihood, and sending it to that individual for you each month, with zero, yes absolutely no, human input required from you whatsoever, at any time?

There are plenty of reports (Wishdesk, Business2, Outbound Engine) corroborating that servicing existing clients is 6 times more cost-effective than acquiring new ones. One of the most effective ways of doing this is through email marketing (Fourth Source), and the best of these uses data you already know about your existing customers.  

Experian produced a report verifying that a personalised email programmes deliver a 6-fold increase in transaction rate and 51% increase in click-through rate. So why are you still reading, why haven’t you signed-up yet?

Email: the most successful go-to digital marketing channel

 Email marketing and websites are popular choices for businesses to use as digital marketing strategies. Both allow digital communication between the customer and the company. 

“We call it digital marketing, but I really think it’s digital sales,” said Jon Borg-Breen, co-founder and head of sales at B2B lead generation agency Symbiont Group. “You’re trying to convert and actually get people to buy something.” 

Businesses such as Pupford, a company that sells dog products, use digital marketing channels such as email and a website to help increase its revenue. 

“If we didn’t have digital marketing, the only sales we’d have would be friends and family and word-of-mouth,” said Marketing Manager Devin Stagg. “It’s our main method of exposure, and all our efforts are pushing us toward getting more revenue.” 

Julian Leaver CEO of Fatface is quoted as asking “If I could find something that knows my customers as well as me I would use it”. So that’s what we built.

The heart of the solution is predictive analytics. Identifying imminent purchases through buying history and then developed by every site visit impressions, by each individual consumer. “When you’ve already captured your customers you’d be a fool to ignore them”, said Clare Shaw, Marketing Manager at Liberty of London.

An amazing insight from a much-admired man Sir Leonard Wolfson said “To have thirteen million people on a database and do nothing with it is what I call strategic constipation”. Argos had that many customers, and never emailed one of them, so he bought the company.

The data-driven version of crystal balls, predictive analytics, can take your business from guessing to acting in a matter of clicks, as long as those are the right clicks. The promise of predictive analytics is that through a fine-tuned statistical model, your business could be ready to take on any challenge. It could know beforehand the necessary volumes of production, client churn rates and even who will be your next colleague. It even promises to detect possible frauds and alert management before this happens. Also, it can optimise marketing through a detailed analysis of the triggers which can cause clients to react positively. 

The speed attribute is offered by the fact that predictive analytics can be performed in real-time. Just feed the data stream into the system and let the predictions flow free. The only downside is that although numbers can be rendered automatically, strategic decisions still require experts.

As one of the sharpest tools in the business analysis kit, predictive analytics, should become more popular for managers. Until now there were important entry barriers, but as technology advances, it will become only a matter of will and understanding of the potential.

Predictive analytics in a nutshell

This is an umbrella term designating different statistical techniques used to make numerical approximations of future outcomes. The data used includes historical records as well as current information, which is sometimes fed to the system directly. Big data and machine learning techniques are used to analyse data, it’s classification: the 3Vs (volume, velocity, variety).

Predictive analytics existed a decade ago, but the underlying tools have changed. It is no longer the work of highly-skilled humans, but that of machines. Of course, the human element retains a role in programming the initial algorithm. Humans will still be in charge of some aspects, they will not become obsolete, just that their role will be more focused on calibrating the algorithm by feeding it with the right data.

Is it for small companies?

As these tools become widely spread, the cost will no longer be restrictive. What was previously only within reach of large corporations will become available even to startups. Assessing uncertainty and preparing for it is most useful for those organizations who have fewer resources to bounce back on.

For small companies, this could also be a growth and competitiveness factor. By using predictions to draft their business plan and better prepare for the future, they stand an improved chance of survival in the long run.

What’s best of all, fully automatic systems do it all for you – no human required.


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Other articles of interest below:
(Index to all articles here)

How to build your database of customers
Missing glaringly obvious opportunities!
Studies on cart abandonment and email retargeting