The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

Luke Turnbull

Luke Turnbull

Luke Turnbull was the Head of Customer and Lead Analytics at Principa, until the end of 2017, after which he returned to his home country of New Zealand. He worked in the financial services industry since 1995, during which time he worked in process, strategy and operational design across a range of organisations in New Zealand, the United Kingdom and South Africa. Luke had been with Principa for 9 years and led consulting engagements with Principa’s local retail clients across the customer lifecycle, with a particular focus on customer engagement and lead generation.

Recent Posts:

Our Top Blogs on Customer Growth and Engagement Solutions for 2017

I have the honour of curating the last of this year’s topic-specific Top Blog Collections. The blogs in my collection all focus on the customer, as we all should(!).

In Customer Engagement, Can You See Like The 3-I Raven?

I have been lucky enough to work with and for various customer facing financial services organisations over the years. One of the benefits of this experience is the chance to compare and contrast how these organisations operate.  Based on some of these observations, I have sketched out a generalised framework that describes the key functional actions of the modern customer-facing organisation. Meet the 3-I Raven*.  

Optimizing Your Marketing Spend

Ever wondered how to calculate the best mix of actions in order to achieve the desired result within budget? You might have a pretty good idea of what mix has worked well in the past, but how much rigour goes into that process? Wouldn’t you like a mathematical approach that eliminates the guesswork?

How Predictive Scoring Is Being Used To Increase Business ROI

As a Marketer or Customer Engagement professional, imagine the cost-savings if you knew who in your database or lead list were likely to be the most profitable customers or most likely to respond? Would you bother mailing a list of a million contacts if you knew that only 100,000 of those contacts were worth targeting and very likely to respond? Innovation is not necessarily the invention of something new, but be the result of finding a new use for an existing product, service, methodology or practice. Take the use of predictive scoring in Marketing. Scoring is no longer only about identifying credit-worthy customers, but is now being used by marketers to identify "target-worthy" leads or customers.

Three Ways Data Improves Customer Retention

The amount of data now available to us is overwhelming: every two days we create as much information as we did from the beginning of time until 2003. As a Marketer, the challenge is determining what data is useful and how to turn it into marketing wisdom that leads to customer retention and growth. Considering that it costs 5 times as much to on-board a customer than it is to retain one, companies would do well to leverage their data to develop and drive retention strategies. In this post, I look at 3 ways data can be used to build and drive customer retention strategies that result in reduced churn rates and open new avenues for meaningful engagement with target markets.

How Marketers Use Machine Learning In Retail

Machine learning is revolutionising how companies are capitalising on Big Data to develop their marketing strategies. While the term encompasses a broad spectrum of technologies and approaches, in a marketing context it can be used to improve targeting, response rates and overall marketing ROI. To put it simply, machine learning involves the automated analysis of large volumes of data – such as consumer spending habits and purchasing behaviour, as well as demographic information – and using a mathematical algorithm and a computer to identify patterns and trends. The algorithm then tests predictions based on historical campaign data and learns from the predictions it gets right. With time, these algorithms become highly accurate as more data from campaign results is added.

How Marketers Can Use Machine Learning To Boost Customer Loyalty

Thanks to mobile technology, wearable devices, social media and the general pervasiveness of the internet, an abundance of new customer information is now available to marketers. This data, if leveraged optimally, can create opportunities for companies to better align their products and services to the fluctuating needs of a demanding market space.

Data Analytics Now Fuels Customer Loyalty In Banking

As the banking industry pursues improved customer engagement, unlocking the value of data becomes critical in designing a successful loyalty programme. The balance of power in banking has changed. What customers expect, how they want to be serviced, what information they are prepared to share, and how loyal they are prepared to be, have all changed radically. According to leading industry analysts, Forrester Research, we are in the age of the customer, in which the only sustainable competitive advantage is knowledge of and engagement with customers.

How To Moneyball Your Customer Loyalty Strategy

If you at all follow the on-goings of Hollywood, you’ve probably heard of a baseball movie starring Brad Pitt that came out a few years ago. Its name is Moneyball, and it relates an important lesson that is revolutionising customer engagement strategies. The movie tells the true story of Billy Beane, general manager of baseball team the Oakland Athletics, who’s sick and tired of their lacklustre performance. After a key loss to the New York Yankees, he’s forced to rebuild the team on a limited budget. Instead of going with the obvious picks, he enlists the help of a Yale economics graduate to crunch the numbers and pick a team of statistically strong yet undervalued players. After a few losses, the data-driven approach is proven effective when the Athletics go on to have a 20 game winning streak – the longest in the history of the game.

How A Local Bank’s Innovation-Drive Elevated The Customer Experience

South Africa’s First National Bank (FNB) has been considered one of the world’s most innovative financial institutions for years now. Voted the most innovative bank globally in 2012, the financial institution owns bragging rights as the first bank in South Africa to launch a mobile banking app in 2011 and second in line to provide fully-fledged web banking portal conveniences to its customers. For  those who can remember the days before feature-rich banking apps,  FNB also carved in-roads to making basic online services available to customers through SMS and WAP services - on what is now considered the archaic cell phones and internet backbones of the early 2000s.

How One Bank Uses Speech Analytics To Improve Customer Loyalty

In order to improve customer loyalty, we need to listen to our customers more. Increasing our share of wallet and maximising customer lifetime value (CLV) will only happen when customers are prepared to choose our brands and products over our competitors. Fortunately, businesses are uncovering clues to improving customer loyalty in new places thanks to data and evolving analytics platforms. This led one bank in Canada to turn to the thousands of conversations between its representatives and its customers for new insights into elevating the customer experience.

Using Speech Analytics To Improve Customer Loyalty

The fact that you are a living, breathing, individual means you have a unique, human-shaped imprint. Be it radiation, the endless trail of dead skin cells, or your infinitesimal gravitational field, you’re leaving a mark that can potentially be reduced to a unit of data and analysed. Enter the human voice: each chortle and hum that emanates from a customer’s vocal chord is unique. This is especially apparent when their voices are converted to electrical signals over the phone – when speaking to your company’s contact centres, for example. And when patterns emerge, such as with certain emotions or excitement levels, intelligent programs can learn to identify human states of mind in real-time speech and act accordingly to improve the speaker’s experience.

How Analytics Is Boosting Profits For Retailers And Restaurateurs

As the pressure of intensifying competition mounts, retailers and restaurateurs are looking to reduce costs across the supply chain while boosting customer loyalty. And with consumer influence now stronger than ever, businesses that fail to respond to the demand for improved products and services will feel the impact on their sales figures. Central to this is the pervasiveness of the social, mobile, analytics and cloud (SMAC) era that is redefining traditional retail models that place the consumer at centre-stage.

A Lesson In Customer And Loyalty Management From Three Yuppies

With virtually every brand setting up shop on social media platforms these days, customers have become immune to seeing “just more marketing” come at them through their screens. But this isn't to  say that social platforms don't have their place in omni-channel marketing. It simply means that maximising your online reach requires a little more than the odd tweet or like. Online communities are an ideal medium for brands to provide customers with a common base to share experiences, discuss news and trends and also discover new value in their brands in the process. South African online kitchenware store – and community - Yuppiechef is a primary example of a business that hit the community management nail on the head, and as a result, has grown into one of the most loved brands in South Africa.

Closing The Loop With Customer Lifetime Value Insights

With marketing budgets increasingly stretched to cover the myriad of channels and touch points out there today, CMOs might feel a little uncertain about whether they’re focusing on the right areas for their acquisition strategies. But even if your marketing spend does deliver positive on-boarding results, it’s still only the first step in a much longer journey with your customer. With the cost of acquiring new business usually five times more expensive than retaining existing customers, and with over 60% of revenue coming from existing customer bases, it only makes sense to build watertight retention strategies that not only retain customers, but preserve the best among them.

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