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How artificial intelligence can help retain customers

How artificial intelligence can help retain customers

It’s a well-known fact that it costs far more to gain a new customer than it does to keep one you already have. In fact, it costs between five and seven times more. It stands to reason, then, that companies that understand the lifetime value of a customer and seek to develop ongoing relationships with existing customers are going to see sales grow more profitably.

But it can’t be left to luck. Many businesses make the mistake of believing that, if their product is good, repeat sales will automatically follow. This can lead these companies to under-invest in retention strategies and force them to over-invest in customer acquisition strategies, to compensate.

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Think about how hard a company like Amazon works to encourage you to make more purchases, once they have you on the website. In fact, Amazon spent $7.2 billion on “marketing” in 2016 alone. Some of that was advertising, to get people to visit the website for the first time, but a significant amount went on getting those customers to stick around or come back. From up-sells and recommended offers, through customer-driven wish lists and subscribe and save deals, to “save for later” functions on your shopping cart, Amazon spends a lot of time and money making its shopping experience sticky and keeping your spending within the Amazon universe.

The difference between companies that grow and outpace their competitors and those that do not is down to the specific retention strategies employed. Let’s look at four of the best for the coming year.

1. Show you care

This is the big one. Studies show that 60% of customer departures are down to indifference on the part of the business. You’ve spent all that money making the sale and simply failed to follow up with some after-sales care and show your customers you appreciate their business. The good news is, this is a fairly easy situation to remedy: you only need do better than “indifference” to reap the rewards and stop customers from leaving.

Businesses can make a difference with as little as an e-mail or a quick courtesy call, asking if the customer enjoyed their purchase and if there is anything else they need. It may add some short-term cost but compared to the cost of acquiring a new customer it’s a drop in the ocean.

2. Recognize your VIPs

This is an area where airlines can teach other businesses a thing or two. Carriers have long understood the value of distinguishing Club Class, Business Class and First class from Coach and offering VIP lounges and services. But to be fair, these customer types self-identify fairly obviously buying the ticket type. How can other types of business identify their VIPs?

If companies can monitor and understand customer intents at every point where they interact with the business, then they can see which ones spend the most, which ones are most likely to post a positive review, or share content about the company. These customers can then be clustered together and targeted for specific deals and rewards.

3. Use predictive analytics

The benefits of developing a clear understanding of long-term customer intents does not stop at identifying the best customers. Business owners can use machine learning equally to head off attrition at the pass. Decision makers cannot be everywhere and sometimes those on the front line are those least able or least empowered to make judgments or decisions about whether a customer may be about to leave.

However, AI solutions can play a role here, since they can be everywhere at once. By pulling in the big data across all interaction points and analyzing the full range of intents, predictive systems can deliver forecasts in order to help business owners learn more about what kind of customer behaviors or concerns immediately precede attrition.

Armed with this knowledge, business owners can tackle the problem at root by modifying the experience that leads to the attrition event. Not only that, but companies can go further still and intercept customers whose behaviors indicate they are about to abandon, offering them incentives to stay.

For example, a customer that searches the site for “delete account” obviously is looking to leave. But that does not mean the customer truly wants to leave. It may simply be that specific concerns they have are not being addressed. When the business fully understands the customer intents it can counter that search with answers to the unspoken questions, such as: “How can I pay less for the service?” or “How can I get a more tailored service?” and so on.

4. Make an emotional connection

Internet and mobile technologies have made it easier than ever to do business at a distance. But while there have been significant cost efficiencies in doing away with the need for physical presence, the result can end up somewhat alienating for customers.

At the end of the day, people want to do business with other people and feel like they are being treated as people. But adding a friendly face doesn’t have to cost the earth. Emotional connections can be made using tone of voice, color branding and multimedia such as video.

AI can play a role here too. Just because you are using machine learning that does not mean the user experience has to become more machine-like. In fact, AI can help “warm up” and humanize the relationship by understanding customer intents better than humans can and effectively “showing empathy”. This means solving customers’ problems before they have even voiced them.

So you can see how the much-vaunted march of the robots is not threatening at all. On the contrary, a more integrated use of sophisticated artificial intelligence applications around business interactions promises to help companies build trust, develop relationships and show the human touch. All of which will do more to retain your best customers than a new advert.

AI is our best chance yet of building a crystal ball

AI is our best chance yet of building a crystal ball

Forget virtual assistants and chatbots, the future of artificial intelligence (AI) and machine learning is seeing into the future.

In recent years we have begun to see how AI applications have established themselves as a staple in business. Alongside cloud computing, big data and mobile internet, AI solutions have found a preliminary use cutting costs on basic interactions and processes.

But their real value going forward is joining the dots between the masses of data points, interactions and captured behaviors to provide accurate predictive analytics. We can’t use a crystal ball to see into the future — but increasingly, we can use AI. Let’s have a look at some of the sectors in which AI is helping businesses see beyond tomorrow.


AI has been making solid strides into banking, aided by the forward thrust of app-based challenger banks and the demands of increasingly mobile consumers. The need for a frictionless mobile experience with a low cost base has meant AI has been able to make inroads across various different areas of the banking world.

In customer service, for example, sophisticated chatbots and virtual assistants are increasingly on hand to parse natural language requests from customers and automate basic processes, such as account opening and closure, or password or login changes.

They can also take some of the hard work out of handling more complex queries, by taking care of preliminary information capture with the customer, before handing off to skilled personnel.

This not only saves time for the customer, resulting in fewer lost sales or abandoned website visits, but can help banks to focus human resource where it is actually needed, with a dramatic effect on cost.

Those same AI skills, however, can also work hard behind the scenes, scanning large amounts of text, such as complex legal documents, and pulling out the key pieces of information, in a fraction of the tile it would have taken trained personnel.

The future of AI in banking, however, will involve a far deeper involvement in risk protection. By effectively joining up the dots between  transactional data and processes, such as electronic identification and verification and know your customer, machine learning can be used to pinpoint high-risk customers, who may need to be screened with Enhanced Due Diligence (EDD) processes, or even predict cyber fraud and head it off at source.

Law enforcement

Of course, any system that can analyze human behavior and forecast fraud is going to appeal to law enforcement agencies. That is exactly what has happened in the UK, according to a piece first published in New Scientist.

West Midlands Police, a British regional force, is reportedly leading the trial of prototype “pre-crime” software called National Data Analytics Solution (NDAS). Driven by recent cuts to funding, the cash-strapped Force is hoping to save money by preventing crime rather than solving it.

The software sends its artificial intelligence algorithms to work with footage from smart cameras around cities and crunch crime statistics to predict the likelihood of someone becoming a victim or a perpetrator of crime — and then intervene.

If that sounds far-fetched, then it’s worth bearing in mind that the system can only work with information that is already out there. In the trial, West Midlands Police mined existing data and statistics from past criminal events to identify some 1,400 potential indicators for crime. The NDAS algorithms then took the data points and learned how to detect crime while analyzing video from metropolitan smart cameras.

Of course, you can’t arrest someone for a crime you only believe they might commit. Or at least, not yet. So the Force is using “soft” interventions such as pre-emptive counseling, in a bid to avert future criminal acts.


The early naughties were all about gathering big data and the insurance industry was no exception. But while some other sectors, such as retail and banking, have forged ahead with analytics to deliver real business intelligence, insurance has been lagging behind. This is set to change, as AI begins to make inroads.

Until now, a lack of adequate tools has meant that the insurance sector has been challenged not only to handle, store and sort the masses of data generated, but also to understand and place an accurate value on what it has gathered. Decent analytics systems have been lacking.

The potential of AI here is evolutionary rather than disruptive and stands to help the sector catch up with banking in key areas such as risk and intents. If pre-purchase behaviors can be correctly identified through analytics software applications such as those marketed by MRP, lost sales can be avoided and customers met with a response at appropriate places on their journey.

AI can also help with identifying and tackling risk. For example, predictive analytics via machine learning can be put to use when it comes to determining whether an applicant is likely to have certain health conditions, or establishing their true driving proficiency.

Market intelligence

Once you begin to understand the potential of algorithms to transform an industry such as insurance it becomes easy to see how predictive analytics could be used across all sectors.

Market analytics firms — ranging from the conservative, survey-based institutions such as Nielsen and Boston Consulting Group to the more creative “futurologists” — make millions of dollars in consultancy every year by providing hard numbers based on past performance and then extrapolating to make predictions about the future.

They help clients to make decisions on anything from outsourcing a business process to entering an overseas market. But until now, all such consultancies have been able to do is look at past performance and hope it will indicate future performance. They are essentially asking clients to take a leap of faith on their own expertise when it comes to forecasts.

AI predictive analysis stands to turn this model on its head by finally delivering that elusive holy grail: the future in numbers. Time will tell.

Five ways to future-proof your startup

Five ways to future-proof your startup

You launched your own business to make money. So as long as you’re generating cash, everything’s fine, right? Well, not quite. The fact that you are successful in business today does not mean you will still be succeeding five years from now.

Markets are in constant flux. The pace of technological change is accelerating and disruptors can come out of nowhere. It can be tempting to take a short view and “make hay while the sun shines”. Examples abound, however, of large companies or even whole industries that were caught out when catastrophic change happened.

This doesn’t have to be you. The smart entrepreneur invests from Day One in strategies that hedge against potential business loss. So let’s walk through five of the most important future-proofing strategies.

Don’t rely on barriers to entry

One of the oldest and best ways to protect a business model is to construct barriers to entry. The idea here is that potential rivals are effectively blocked from competing because of the difficulty in entering a given market.

Barriers can be financial. For example, it was once extremely difficult to enter the road logistics market because of the high cost of acquiring and maintaining a fleet of trucks. However, the market today is highly fragmented. Shared warehousing has reduced barriers to entry and today many third-party logistics providers outsource the last-mile piece to a vast network of self-employed delivery drivers who own their own vehicles.

Barriers might also be regulatory. Until January 2018, banks in Europe could rely on their license to keep competitors away from lucrative payment services. However, the EU Open Banking Directive has forced banks to open up their payment APIs to third parties, allowing tech companies with no banking license to compete for payments, often undercutting the banks. The US currently does not have such a piece of legislation but given the lobbying power of the software giants, is it realistic to imagine this will continue forever?

Other barriers could include expertise, but even if skills cannot be developed, they can be bought or made obsolete by disruptive innovation. By all means try to build a wall, but the best you can hope for is a temporary monopoly. In a free market, most barriers will come down eventually. Have a plan for that time.

Don’t be a single-niche business

It’s likely you started in business because you did one thing better than anyone else. While a niche strategy is indeed a smart way to get started, relying on that single niche carries risk. Think about CD makers. In under a decade, compact discs went from rapid growth to terminal decline. The model was disrupted firstly by download retailers such as Apple’s iTunes, then by streaming services such as Spotify.

Instead, follow Amazon’s lead. The retailer mastered a simple technique called “productize and scale”. Jeff Bezos started a printed book retailer but he was able to significantly scale his business. He did this not just by adding new retail categories but by packaging up the core fulfillment and logistics infrastructure as a product to sell to third-party traders on Amazon Marketplace. This simple move allowed Amazon to go from running its own distance selling business to taking a share of everyone’s distance selling business.

Next, the company packaged up its web expertise as Amazon Web Services. AWS is now a global force in web hosting. So if the market for printed books declines, Amazon won’t worry too much. The chances are, you have additional expertise that you can productize and scale.

3) Don’t just watch your own industry

If you want to future-proof your startup, you certainly need keep a sharp eye on developments in your industry. This means watching your competitors, your customers and your suppliers. However, many businesses make the mistake of stopping there. The trouble with that strategy is, most disruption comes from outside the industry it affects.

For example, Kodak was once a billion-dollar company, selling cameras and film. Unfortunately, Kodak was looking the other way when the smartphone arrived. Who would have thought everyone would have a digital camera on their phone? Clearly Kodak never imagined it. The company filed for bankruptcy in 2012, just five years after Apple launched the first iPhone.

To successfully identify threats and risk, business owners of all stripes need to conduct regular PESTEL analysis to keep up with factors in the environment that could impact their trade.

4) Create a finance department

One competency that often separates the large firm from the startup is the existence of a finance function. In many small businesses, “finance” is limited to keeping the books and preparing accounts.

In fact, the role of finance should not stop there. An effective finance department works proactively to source, move, trade, invest and spend money in the most beneficial way.

If you think this is beyond you, think again. Today, entrepreneurs can train themselves to manage money from the comfort of their own computer. Learning over the internet has reduced the time and investment barriers: small business owners can now easily afford one of the many online trading courses available from specialist providers.

Some businesses become so adept at financial management that they are able to productize and scale their investment services as consultancy or even spin them off for profit. In April 2018, Chinese internet giant Baidu Inc. span off its financial services arm to focus on search and artificial intelligence.

5) Listen to customers and track their behavior

It’s the most simple strategy but the easiest to overlook. Sometimes, busy entrepreneurs can focus so much on sales or product innovation that they forget to talk with their customers. In hindsight it seems obvious, but so many brick and mortar retailers ignored the threat of e-commerce and paid the price. Asking simple questions today about your customers’ habits and preferences can help you see tomorrow’s big change coming — and help you meet threats head on.

Learn these four essentials before you start investing

Learn these four essentials before you start investing

If you’re thinking of making your first investment it’s natural to hesitate. You may be thinking: is this the right time to buy? Prices go up and down and if you don’t have experience of following the tickers it can be hard to know whether or not you’re about to make a mistake.

Well, the good news is there are four essential pillars that should be in place before you commit a penny of your hard-earned cash. Get these right first and you’ll be on the road to making the right choices with your money.

Step one: how much time do you have?

The most basic mistake a novice can make is to invest without a plan. You wouldn’t set out on a road trip without knowing where you want to end up, so before you commit your funds, you’ll want out figure out your end game. Knowing how much money you want to make is only one side of the coin.

On the flip side, you need to figure out how much time you have to make that money. For example, are you going to need funds in 10 years when Junior goes to college, or do you need cash soon to meet an IRS demand? Your personal situation is going to determine the route you take. Once you know how much time you have, you can ask yourself the next question.

Step two: how much risk can you handle?

There’s an adage that you should never gamble more than you can afford to lose. That said, some investments are riskier than others. Once you know your end game, you’re going to want to assess your own appetite for risk.

When it comes to investing, there’s a well-documented relationship between time, risk and reward. Your own tolerance for risk is probably one of the most important factors in your success so, rather than guess, you should look to the end game you already set yourself to help you figure this out.

For example, the more time you have to reach your goal, the more you can afford to take a risk, as the longer you keep your money invested, the more time there is to recover from any down markets or bad stock picks.

There’s even better news. Time is not only on your side when it comes to reducing risk. Having more time can also bring greater rewards. This is because the longer you have to reach your goals, the more you stand to grow your returns exponentially from compounding your earnings.

On the other hand, if you only have a short time to reach your target, then you’re better off going with a safer investment.

Step three: spread your risk

There’s a reason we don’t put all our eggs in one basket. If the basket falls … Well, you get the picture. No matter how well you figure out how much time and risk you have to play with, any potential rewards are negatively impacted if you simply stick with one stock, one industry or one asset type.

Once you figure out your appetite for risk you can begin to allocate your funds to different asset classes. This is where some initial investor education is critical, because it literally pays to know which types of investment hold the greatest risks and the greatest potential rewards. Here are the three main asset classes:

Cash and money market funds. Your main goal here is stability. This is a very safe investment, meaning you are unlikely to lose money, but the returns are small. The main risk here is that you could earn money more slowly than inflation rises.

Bonds and bond funds. This is the investor’s middle ground. Examples might be US government bonds or international bonds. The goal with this type of asset is to get a moderate return for a slightly higher risk. The main risk here is due to the fact that bond prices fall as inflation rises. This means that if inflation rises too far, the issuer may not pay promised dividends or be unable to pay you back your principal.

Stocks and stock funds. This is the riskiest type of investment but brings the greatest potential reward. The risk here is around falling stock prices, due to poor company performance or negative market sentiment. The stock market is very jittery and sentiment can be affected by all kinds of adverse news stories, political events far away and sometimes even the weather. To add to this, falls in stock prices can be much deeper than falls in bond prices.

So these are you main classes of asset. If you had a very long time to reach your investment goals you light get away with a stock-only portfolio, but as a general rule, when allocating your funds, it pays to spread them across all three investment classes. There is no magic formula here, the mix will depend upon your own personal appetite for risk and your personal end game.

As well as spreading your investment across asset classes, when building your portfolio, it pays to spread within asset classes. For example, domestic and international currency or bonds, varying industry types and so on.

Step four: understand your costs

So now here’s the bad news. Every investment comes with a price tag and, even worse, the money that you pay out to costs will compound over time. For example, paying 2% of your principal investment may not seem like much of a loss, but once your returns start compounding, 2% is going to be a lot more money.

So it’s critical to understand what you’re paying and how to manage your costs. Counter-intuitively, funds with lower costs tend to outperform those with higher costs.

So, if you’re wondering if it’s the right time to invest ask yourself: have I ticked off this four-point checklist? If the answer’s yes, well there’s no time like the present.

The end of hypermarkets

The end of hypermarkets

Is it over for hypermarkets?

Increasingly urban, time-pressed and tech-savvy, consumers are shopping ever smarter and closer to home. In this context, has the hypermarket become irrelevant? We ask three senior retail analysts.

Spend enough time poring over company reports and financial statements and patterns will begin to emerge. Or, at least, it can seem that way.

About a year ago we began to suspect all was not wholly well with the hypermarket channel in Western Europe. The source of the hunch was negative sales growth or softness revealed in company financial reports or market data, but a trend was far from proven. Our feeling, given other trends impacting the market, was that the channel was probably losing traffic to proximity formats, which have been improving their penetration, their sophistication and their value proposition, or to convenient models such as click and collect. It stood to reason, but proof was elusive. The hypermarket remains the single most important volume channel for consumer packaged goods, so clarity on the health and future of the format is needed. We decided to dig for data.

It took a while, but some finally came in October 2010. Nielsen revealed some numbers at a trade event in Berlin, showing that hypermarket turnover per store in Europe had fallen by 7% on average over the last few years, across a sample of 20 countries. This was the first time we had seen any quantitative data on the subject. Presenting the figures, Jean-Jacques Vandenheede,  Nielsen Director of Retailer Insights, Europe, said hypermarkets had suffered in recent times. “There is a need to reinvigorate the hypermarket,” he told delegates.

Expert panel
In discussion now with Delevine Media, Vandenheede offers some theory on what might be causing the decline: “I think that the first issue is shopper missions. At different times shoppers have different shopping intentions: do I need a lot? Do I need something quickly? How much time do I have?  Shoppers will reconcile shopping missions with the most appropriate store. A big tendency is that urgent, immediate needs have gained over time.”

Joining the conversation is Natalie Berg, global research director at Planet Retail. Could recent price deflation account for some of the turnover decline? “Hypermarkets used to win on price and assortment,” Berg says. “Today we have discounters and the internet. So, yes partly price deflation in certain categories like electronics. However, it’s more a case of shoppers defecting to other more relevant channels such as discounters and c-stores, as well as online. The concept is dated.”

In what way, we wonder. “Consumers used to venture out of town to hypermarkets for low prices,” Berg explains. “However, today the blurring of discount and convenience means that low prices are readily available on the high street, leaving little incentive to travel to hypermarkets. Similarly, online continues to gain momentum throughout Europe, bringing all of the products (and more) and prices typically available in a hypermarket right to the consumer’s home.”

Vincent Verdier, director of insight consultancy at Kantar Retail, concurs with Berg and Vandenheede, but adds a proviso: “If you look at the blunt data over, let’s say, five to ten years, then yes the channel is losing share. That’s a fact. So, on that basis I would agree 100% with Jean-Jacques and Natalie. But are all hypermarket retailers doomed? No, I don’t think that’s the case.” Citing market share figures from Kantar Worldpanel, Verdier says that the downward trend is not evenly spread across the channel, even in Western Europe, where the format originated. “Some hypermarket operators are having trouble, while there is some growth being witnessed for others: Leclerc, Tesco Extra, Kaufland for example. Hypermarket is the fastest-growing channel in Russia and as far south as Turkey it’s not declining.”

“Western Europe is the problem child,” Natalie Berg says, adding weight to this argument. “The market is saturated and legislative restraints make it virtually impossible to open new stores. There is still plenty of growth for hypermarkets in emerging markets, but we are likely to see a new wave of expansion through the compact hypermarket format. Despite trading from a smaller footprint, compact hypers tend to be just as profitable as a traditional hypermarket. The advantages? Lower operating costs means lower prices, which enables retailers to reach out new consumers in areas that may not otherwise support a full hypermarket. Walmart has had tons of success with this in Latin America and they just opened their first one in China.”

Vandenheede also downplays the idea of a universal downward trend: “This chart is made up from trends in 20 countries: in each of these countries there are specific situations every year.”

The future
So what conclusions and strategies can we draw from this? Should retailers continue to invest in the channel in the face of traffic decline, and should brand manufacturers be worried? Vincent Verdier says the future of the hypermarket channel is a key topic for the majority of his clients. “Competition has heated up, but while the format is being challenged by more convenient, simpler and faster shopping trips and concepts, it is important to remember that hypers continue to deliver some sort of growth nevertheless.”

He points to recent examples of hypermarket operators innovating: “Casino is trying by improving its Géant layout and assortment, and obviously Carrefour is rolling out Planet,” a concept that attempts to boldly re-imagine the hypermarket shopping experience. Verdier adds: “The point is that hyper continues to deliver huge majority of sales for branded manufacturers; hence it is impossible to simply walk away from it.”

Natalie Berg develops this argument by saying successful retailers must adopt a multichannel strategy. “There is no such thing as a hypermarket shopper or a convenience store shopper. Retailers must be able to reach their customers on different shopping occasions, whether that is in a big-box out of town or while shopping on their mobile phones … Hypermarkets must create a more compelling reason to shop. The most basic rule in retailing is staying relevant to your customers.”

Jean-Jacques Vandenheede underlines the axiom that consumers don’t shop by channel: “Shopping missions are the key. Shoppers will not put in balance a trip to a hypermarket with a trip to convenience. The mission will define where to shop. Hypermarkets need to give shoppers the arguments and incentives they can’t refuse.”

That sounds like consensus. But with ongoing socio-economic trends pointing to more single households and more urban living, those incentives had better be compelling.