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4 Lessons From Great Customer Retention Strategies On Reducing Churn

March 6, 2018 at 11:41 AM

As the pressure of intensifying competition mounts every day, companies must look to boost customer loyalty, considering that it costs five times as much to onboard a customer than it is to retain one. And with consumer influence now stronger than ever, businesses that fail to respond to their customers’ needs will feel the impact on their sales figures. A recent study by Bain & Company revealed a 10% increase in customer retention levels results in a 30% increase in the value of a company, and a 5% increase in customer retention rates increases profits by between 25 and 95%.

Central to this is the pervasiveness of the social, mobile, analytics and cloud era that is redefining traditional retail models that place the consumer at centre-stage.

It seems that the key to achieving a competitive edge in the modern age is to identify opportunities that enable the shift toward customer-focused and data-driven business models. (Click to Tweet!

In this blog post, we look at some great examples of customer retention strategies in action and how you can apply these same strategies in your business every day.

Jet Blue’s People Officer

On specific Jet Blue (an American low-cost carrier) flights, a People Officer stands up mid-flight and starts interacting with passengers. The officer hands out free flight tickets to passengers who correctly answer the trivia questions asked, and in between the free giveaways, asks passengers for suggestions, concerns, compliments and complaints.

The goal of the People Officer was twofold: to impart goodwill towards the carrier, but also to listen. Identifying suggestions or complaints was the primary goal. By determining what your customers want and listening to their needs, you can work towards delivering a better service or product.

How to implement in your business:

While doing a giveaway can't be done on a frequent basis, you can easily achieve the primary purpose behind this strategy: gathering information. If you have any customer data available, you can use data analytics to identify patterns and develop strategies that will see you reducing churn. Customer analytics involves using your data to understand your customers, segment them and engage with them more relevantly and effectively. 

Pizza Hut’s “welcome back” pizza

There’s a Pizza Hut branch who had a regular customer with whom the employees had built up a relationship. When the customer didn’t place an order for two weeks, the concerned employees phoned him up and asked whether he was okay, since they hadn’t heard from him. When he confirmed he was fine, they promptly sent him a free “welcome back” pizza and turned an already loyal customer into a complete evangelist. He, of course, shared the story on social media, and Pizza Hut got some good press from it.

How to implement this in your business:

You don’t want to rely on customers suddenly going AWOL to get this good vibe towards your brand. But don’t worry, you have some other options. Just like this Pizza Hut Branch, you have access to all your customers’ spending and buying habits: just on a much larger scale. Use machine learning or advanced algorithms to detect when customers are dropping off, when other customers are likely to drop off and what you can do to encourage them to stay (and how effective each of your efforts is). It's good to note that the Pizza Hut didn't send free pizzas to every one of their customers – just one they thought they might be losing. You should do the same by making exclusive offers only to customers who have a high risk of churning.

Casper’s companion for insomniacs

Casper, an American mattress company, released a free chatbot to keep insomniacs company during the early hours of the morning (or whenever they felt like a chat). All the chatbot did was simulate real conversation, but it was also collecting cellphone numbers for lead generation purposes. Any insomniacs were sent promotional messages and discounts to purchase a new, comfortable mattress. The chatbot generated $100 million in sales within the first year.

How can I implement this in my business?

The takeaway from this story is that AI will help you increase your revenue. Creating a chatbot to ease payments, place orders or make suggestions, is a great idea and will help your business retain customers. You can also use AI in different ways, e.g. as a coaching bot in your customer service, sales or collections call centres. An AI-driven coaching bot can make recommendations for treatment based on the data available. 

Hyatt’s Upsell Recommendations

In 2015, the Hyatt Group announced that it had aligned its operations to use predictive analytics to improve cross- and up-selling to guests at their 500-plus hotels across the globe.

By analysing guest history and preferences and comparing them to those of guests with similar profiles, Hyatt is able to automatically display relevant messages that tell desk agents that the guest they are checking in is likely to want to upgrade their room to one with a view, or might want to know more about amenities the hotel offers.

According to the group’s SVP for Strategy and Analysis, Chris Brogan, In 2014 in the Americas, we rolled out a program that has increased the average incremental room revenue, post-reservation, by 60%, 2014 versus 2013. That’s compared with similar programs in the past that lacked the sophisticated analytics.” Among Hyatt's chief data sources was its membership program that gave the group the per-individual insights they needed to offer exclusive discounts or amenities, based on a particular member's past travelling, accommodation and other preferences. The success of the group’s initial foray into big data in the Americas has led to the decision to adopt the predictive model on a global scale.

How to do the same with your business:

You can do just that: use predictive analytics and machine learning to identify potential upsell and cross-sell opportunities, based on the data that you already have available.

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 businesses. This data, if leveraged optimally, can create opportunities for companies to better align their customer service to the fluctuating needs of a demanding market space. So why don’t you?

using data analytics for customer engagement

Mark Roberts
Mark Roberts
Mark has over 15 years’ experience within the credit life cycle with 10 years’ specialised in Collections and Recoveries having been gained through exposure in both B2B and B2C markets across Europe, UK, and South Africa. With both extensive operational and strategic experience, Mark has successfully delivered and lead a number of initiatives within collection strategy, operating processes, platforms, and payment solutions. He holds a B.Comm degree in Actuarial Sciences from University of Pretoria.

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Coverage ratios are worked out considering the loan/facility that is being applied for. Finally, liquidity ratios indicate the ability for a company to convert its assets into cash. There are a variety of ratios used here. The current ratio is simply the ratio of assets to liabilities. The quick ratio is the ability for the business to pay its current debts off with readily available assets. The higher the liquidity ratios the better. Ratios are used both within credit scorecards as well as within policy rules. You can read more about these ratios here.   5) Size of loan When assessing credit risk for a consumer, the risk of the consumer does not normally change with the change of loan amount or facility (subject to the consumer passing affordability criteria). With business loans, loan amounts can range quite dramatically, and the risk of the applicant is normally tied to the loan amount requested. 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In the graph below the performance of an industry is tracked for two years and then projected over the next 6 months; this is then compared to the country’s GDP. As the industry appears to track above the projected GDP, a positive outlook is given to this applicant and this may affect them favourably in the credit application.                   7) Risk of Region   The last area of assessment is risk of region. Of the seven, this one is used the least. Here businesses,  either on book or on the bureau, are assessed against their geo-code. Each geo-code is clustered, and the projected outlook is given as positive, static or negative. As with industry this can be used within the assessment process as a policy rule or within a scorecard.   Bringing the seven risk categories together in a risk assessment These seven risk assessment categories are all important in the risk assessment process. How you bring it all together is critical. 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