Month: January 2014

Daniel Nugent (pictured) offers top tips on customer retention.

Customer retention is incredibly important for growing a sustainable business but as consumers we can often feel that the best deals and incentives are reserved for new customers, and efforts to secure our loyalty and repeat business are secondary.

Things are changing though, due to the high cost of bringing in new customers. Studies, such as that by Lee Resources Inc, show repeatedly that it costs businesses five times as much to acquire new customers as it does to keep those they already have. Today, many more businesses are looking specifically to introduce programmes that focus on engaging with their current customers in order to develop strength in the relationship and ultimately retain them. Get it right, and these customers can become key brand ambassadors, helping to bring in new customers from among their friends, family and acquaintances.

Using loyalty or reward schemes is one way to retain customers. Here are some top tips on how to make the most of them in order to establish a long-term relationship.

1. Consistent communication is key

If your customers are entitled to be part of your reward scheme, work hard to achieve understanding from them so they are clear why they are being given the reward and what value it holds for them. Relate it to their current requirements and remind them frequently that they have the benefit.

2. Relevance is king

The reward on offer must be relevant to your consumers’ requirements, interests and aspirations and it must compliment your brand. Over recent years, given that many consumers have had to tighten their purse strings, those brands that have been successful in engendering loyalty are those offering rewards and discounts that are relevant in terms of product, brand and timing. For example, those that repay consumers for the shopping they would already be doing, such as the weekly supermarket shop, as well as the bigger ticket and perhaps more luxurious expenditures such as the annual holiday. We see engagement levels more than three times higher in reward programmes where the rewards, offers and associated messages and information are fully aligned with the interests and needs of their audience, than in similar programmes that lack this relevance.

3. Keep it simple

Don’t overcomplicate the rewards programme as your customers may not understand it and will not engage with it. We have all been confused and frustrated when we are unable to take up a seemingly good deal because of the restrictive terms and conditions. Presenting consistent offers which offer the greatest level of flexibility and are not limited in number or by when an individual can use them, rather than one-off deals that are available for a fixed period of time, helps to engage customers with the brand and establish a long-term relationship.

4. Stay fresh

Keep the reward programme evolving and interesting by offering new rewards and opportunities to ensure customers don’t become tired of it and to show you have an ongoing interest in their lives. This can increase repeat purchase and build loyalty, as well as giving you a reason to communicate more and therefore collect valuable data. However, customers won’t be happy if a popular offer is suddenly removed – so, refreshing a scheme needs to be done gradually to ensure the audience is not alienated by an abrupt change and loss of familiarity. As a general rule, around 10-20 per cent should be changed per month.

5. Stand out from the crowd

To achieve stand-out from other reward or loyalty schemes, it is important to reward your customers with something that is not readily available elsewhere. If you can deliver better value than those offers and discounts that are freely available on group discount and other general public websites, then your consumers will take notice.

6. Make sure you listen

Remaining in constant two-way communication with your consumers is key. If they feel they have a voice they will be far more engaged. The programmes we operate that have the highest levels of customer engagement are those that proactively seek feedback and input from their customers. Allowing them to feel they are shaping their reward package through feedback and suggestions will tell you exactly what they like and don’t like about the current offering. Even if a scheme cannot offer everything the customer says they want, if they see it evolving based on their comments they are far more likely to feel valued.

Consumers will engage with your loyalty or reward scheme if it is presented in a way that is relevant and offers real value to them, and the right scheme can be instrumental in turning a customer’s first purchase into a long-term relationship.

Daniel Nugent is head of Entice Loyalty.

Kevin May (pictured) examines the passing of privacy and the hugeness of data.

In the cash economy preceding the era of the big banks, people kept their tokens of material wealth hidden under mattresses and inside teapots.

When the first banks came along, they needed to build visibly stout buildings and fortified vaults so everyone could feel their money was not just secure, but positively safer than squirrelled away in some hidey-hole at home.

In many respects, money then is like data now. It’s valuable, personal and most people want to stop others getting hold of theirs. It’s also become a key driver of the economy and there’s a whole load of it about.

To describe it as ‘big’ is one of the more extraordinary understatements of our age. Digital data today is not even colossal, it’s incomprehensible. The volume is more overwhelming than ever, and the ‘velocity’ – how quickly it’s accumulating – is increasing all the time. IBM estimates that 25 quintillion bytes of fresh data are generated every day, which extrapolates to 90% of all data ever created coming into existence in just the last two years.

Corralling this data and figuring out how to interpret it is predicted to be a $47 billion industry by 2017. And that scares the pants off most normal folk. This isn’t just down to the counterpart industry that has emerged to terrify us with the seeming inevitability of identity theft for all, or the high-profile news of the damage that can be wreaked by someone as low-ranking as an Edward Snowden, or even the catastrophic adventures of Carlos Danger et al.

It is as much down to the realisation that our modern lives are increasingly beholden to technologies that translate all the stuff that really matters to us into bytes, and that none of this ever goes away. The idea that somewhere a continuous record is being laid down about your individual life accessible in perpetuity by others is something many find very disconcerting.

It boils down to integrity, both physical and logical. Physical integrity is about creating systems that can scale to handle the profusion of data, and the trade-offs that are required in the balance between making the data constantly available across a number of platforms while keeping it secure (especially when outside vendors become involved).

Logical integrity on the other hand deals with questions of correlatedness, privacy and freshness. But even with all this in place, the fear is for the sort of dystopian future represented by Dave Eggers in The Circle, where tech companies turn our every online movement into detailed report cards for profiteering corporations.

While it can be tempting to rue the passing of all privacy, is the paranoia really justified? In essence, this is a systematic analysis of huge volumes of data to find patterns, insights and related behaviours. The data are everything from downstream clicks, comment threads, stock market fluctuations, online purchase transactions, to the GPS co-ordinates tagged in Instagram photos. The individual’s information isn’t what’s being analysed, but rather collective shifts of Internet activity. These seemingly disparate clicks can identify trends in social sharing, shopping preferences and purchase frequencies.

In principle, it seems not much different from the sort of quantitative research that marketers have been using for decades to inform strategies and decisions. There is no value in the data at an individual level, but only as a collective picture of the whole. But some things have changed. What separates Big Data from past analytics is not just its volume and velocity, but also its variety. This third V is what allows businesses to understand their customers better, with a more reliable and holistic view of their behaviour than ever before.

This new variety has enabled technological breakthroughs that people benefit from without even realising it. The Google autocomplete feature, Netflix recommendations, the cupid service of Match.com and the real-time intelligence of the iPhone’s Siri are all the result of Big Data algorithms.

Big Data has actually reduced rates of identity theft, as financial software scrolls through billions of transactions and alerts staff to investigate spending anomalies. Software company Intuit has set another virtuous example by publishing ‘Data Steward Principles’ and making structured data available to help customers themselves become better educated on spending habits.

The Institute for the Future’s Jerry Michalski believes the collaboration of sensible minds and empirical data is the key to social and commercial progress: “When crowds of people work openly with one another around real data, they can make real progress. See Wikipedia, OpenStreetMap, CureTogether, PatientsLikeMe . . . Big Data has found remarkably simple answers to thorny problems.”

One of the reasons why Big Data gets such a harsh press is because nobody ever uses the term except when things go wrong. If things run smoothly and life is easier, then the credit goes to individual brands. That credit translates into trust – and here lies the crux of the issue.

Digital customers have greater power than ever before to make or break brands and creating trust is becoming much more than just a question of warm and fuzzy feelings. Like the early banks, how strong you build your fortress is going to have a substantial say in how full your vault becomes.

Kevin May is founding partner at Sticks.

Sean Murphy (pictured) explains how analytics can enable companies to accurately and efficiently identify customer issues and take immediate action to resolve them, retaining customers and pinpointing new business opportunities.   Companies are under increasing pressure to deliver the highest quality customer experience.

Competition for customer mind-share is fierce, while at the same time loyalty is more elusive than ever – one poor customer experience will have the consumer switching to the competition without a second thought.

We’re now in a 24/7 world where one negative tweet or blog post can go viral in a matter of hours. Content like this gets picked up by websites, read by thousands, re-tweeted and commented on. For this very reason, the customer experience has become a major concern for organisations. It is essential that operations have the means to detect potentially unsatisfactory situations and have the facilities to act on this information immediately. An organisation can then respond in the right way to strengthen the customer relationship and brand – and limit the damage. Once the correct action is taken, it is also important to measure the effectiveness of that action – with the help of sophisticated analytics.

Quality monitoring in the contact centre is nothing new. The vast majority of companies have been using call recording and monitoring systems for some time, but those systems and processes usually only provide a partial picture of what is happening by manually reviewing only small, randomly selected samplings of calls. Having quality analysts manually listen to calls is labour intensive and therefore it’s a very expensive process, which limits the number of calls that can be monitored. Hence, most organisations only review a small fraction of the calls handled by their organisation, with the industry average being to review around one or two percent of calls. If other types of interactions such as email, chat and/or social media are included, the fraction of the organisation’s conversations with customers or prospects that are reviewed becomes even smaller.

At the same time, enormous business opportunities are hidden within those conversations. The information that can be extracted from conversations with customers and prospects is invaluable in understanding the customer service experience. Organisations must engage in strategic process improvements that go beyond selective samplings of recorded communications.

Analytics in a customer-centric organisation

Rather than a lack of data, the challenge lies in the ability to extract the ‘nuggets of gold’ from within that wealth of information efficiently and effectively and make those insights actionable to deliver meaningful results.

New innovations in analytics such as Speech Analytics and Text Analytics can transform customer service by analysing all conversations with customers or prospects over all channels including calls, emails, chats, and social media. Web-based dashboards enable ongoing visibility across all conversations and agents, giving today’s contact centre manager new levels of insight to optimise their workforce, identifying those interactions that need immediate action and then routing the customer to the optimal agent, back office worker or manager for resolution.

We have found at Genesys that our conversation analytics solutions enable organisations to analyse the variation of journeys by customer, tier or issue, as well as being better informed to contextualise and personalise end to end experiences, improving satisfaction and long term loyalty. This enables organisations to reduce costs, enhance sales and most importantly improve the customer experience. Such analytics can help improve the contact centre in many ways.

The benefits of conversation analytics

1. Understanding why customers have got in contact: Speech Analytics and Text Analytics can comprehensively categorise all interactions to identify the reasons why the customer has got in contact with the organisation and the processes in place that drive those interactions. Analytics allow contact centres to determine the appropriate action and measure its effectiveness as well as identify contacts that might be better handled using cheaper self-service options.
2. Improve agent work quality more efficiently and effectively: Speech Analytics overcomes the challenges inherent in traditional Quality Management systems and processes by automatically monitoring 100% of calls, as opposed to the small fraction that can be reviewed with traditional manual methods. In addition, because evaluation criteria must be objectively defined according to phrases used within conversations, human subjectivity is eliminated from the process. When Text Analytics is unified with Speech Analytics, all conversations across all channels of contact can be evaluated in exactly the same way.
3. Understand the root causes of customer dissatisfaction: Analytics can help identify the underlying causes of customer frustration by identifying the specific business processes, products, services or agents which are producing customer dissatisfaction.
4. Improve the effectiveness of sales, up-selling and cross-selling: Organisations are increasingly encouraging their agents to use up-selling and cross-selling techniques. However, the sales techniques which are most effective can differ markedly depending on the product or service being sold. The techniques which are most effective for each specific situation can be identified by analytics, then agents can be trained when to use each technique within conversations. These conversations can then be continuously monitored to ensure that agents are properly using the techniques they’ve learned.
5. Proactively discover emerging trends within the Voice of the Customer: Most organisations are already aware of the most important Key Performance Indicators and agent and customer behaviours that are important to measure and monitor on an ongoing basis. However, even the most technologically advanced analytical systems usually need to be told by humans what to analyse, so if the organisation doesn’t already know that they need to be on the lookout for a particular issue, most analytical systems are equally unaware of such ‘unknown’ issues. Speech Analytics and Text Analytics can automatically discover emerging trends or issues within the voice of the customer by analysing all conversations and uncovering relevant topics that customers are suddenly talking more frequently about. These ‘automatic discovery analytics’ can then proactively alert organisations about issues with their products or services which the organisation may not have been previously aware of.

So, what’s the conclusion?

Customer service operations need to start moving to more holistic measurement programmes for communication channels and touch points, to understand the customer journey end-to-end and completely understand all conversations the organisation is having with customer and prospects. By analysing all conversations and capturing the Voice of the Customer across all channels, organisations can begin to accurately measure customer loyalty, understand and validate what is driving customer satisfaction, while identifying areas of improvement.

As new business challenges emerge, analytics play a vital role in helping organisations identify and address problems with customer experience before it significantly impacts customer retention. Sean Murphy is director of Product Marketing at Genesys.