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It’s time for mail to make a return – Why direct mail can still be an asset for financial brands

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It’s time for mail to make a return - Why direct mail can still be an asset for financial brands

At the end of the Nineteenth Century, 100,000 prospectors struck out for the Klondike wilderness in search of gold. Although a third reached their destination, just 4,000 came away with their prize. It was a poor return that today’s digital marketers might do well to remember. 

Like most other industries around the world, financial services has joined the digital marketing gold rush. In pursuit of new customers, UK brands alone were predicted to spend £1.6bn on digital marketing during 2018; well over 10% of the national total (eMarketer). It’s understandable. There are relatively low costs of entry with digital campaigns – particularly for paid search advertising, or pay-per-click (PPC) – and much can be automated. 

But things are changing. Google and its search rivals have seen brands from all sectors falling over themselves to invest in PPC. Adhering to the laws of supply and demand, the online media giants have gradually inflated prices. One study showed PPC costs more than doubled per keyword between 2014 and 2016 (Hochman Consultants). Meanwhile, the forthcoming EU Privacy and Electronic Communications Regulations (PECR) might further rein in digital marketing. 

Champions of traditional marketing – like me – believe digital’s loss can be direct mail’s gain. 

From the last post to a new dawn?

There’s a widely accepted marketing myth that the cost of running a direct mail campaign far outstrips digital fees. With search engines putting up their prices the gap is closing fast. It’s true that mail isn’t the cheapest medium. However, the fact that financial services is one of a handful of sectors where products can command high margins makes post an attractive prospect.

 The number of mailings the average British household receives has dropped from around 60 to merely a handful a week. Conversely – perhaps because it has become something of a novelty to consumers – it’s also growing in popularity. According to recent research from the Direct Marketing Association (UK), a third of consumers say direct mail is the most effective channel when brands want them to buy products or services (DMA Customer Engagement Report 2019). Small wonder – there are lots of benefits, and here are just a few:

 Good prospects. Mail is great at persuading people who are already enthusiastic about your brand to take the plunge and buy. Response rates range from 10 to 30 times higher than those for digital marketing. Moreover, including mail in the marketing mix can boost response to other channels used in the same campaign by a fifth (Marketing Metrix). With digital, conversion rates and lifetime value are low.

 Mail loves digital. There’s evidence to suggest (not least from the UK’s new industry measurement bodyJICMAIL and Royal Mail) that using mail and digital together can significantly boost engagement and response: by up to 62%, in fact. So it’s not wholly about ditching one for the other; the two (and other channels) can work in harmony. It’s what those in the know refer to as the tongue-twisting ‘complementarity’.

 The long game. There are fewer industries with more complex propositions than financial services. The good news is that brands can simplify their products with several pages of finely crafted copy. Mail doesn’t suffer from the restrictions of the classified ad-like search results page so, ensuring you stay relevant, you can make your point in a more explanatory fashion.

 Mailing data is king. If PECR is set to make digital marketing more difficult, the recently implemented EU General Data Protection Regulation (GDPR) seems to be having the opposite effect. The new laws have forced marketers to clean their databases, so those turning to mail can do so safe in the knowledge that the vast majority of their customers and prospects want to receive their postal communications.

 Beyond the doormat. It might sound surprising, but mailpacks garner on average eight minutes of attention from each recipient – a figure digital marketers can only dream of. And it’s not just welcomed by the traditional over-55 audience; DMA (UK) research points to mail’s resurgence among 16- to 34-year-olds. Don’t forget to target them.

It’s time for mail to make a return

In all of this, it’s important to realise that creating direct mail isn’t as simple as it looks. 

But it’s worth the effort. The return from a well-crafted mailing is astonishing. Simply by changing the copy and the stuff inside the envelope you can see 50% improvement in response. I did a mailing for a wine company that produced no less than an 80% uplift. Nothing else changed – just the way you tell the story. 

Yet writing well is hard. A four-page letter will turn off most recipients after a few paragraphs if the copy is flabby and functional, even if they are interested in the product. 

And think about making sure you use the postage you’re paying for. A C5 window envelope with a couple of sheets of paper inside is like booking a 60-second TV commercial and only running a 15-second ad in the space. Why leave the blanks? You’re paying for it – and the more information you get into that envelope, the better the result you’ll get. 

Another common mistake is the missing call to action. Get to the point right away, tell the consumer what they need to do and repeat the command often. Above all, be creative. 

In their quest for quick wins, brands began to overlook tried and tested methods, rushing online and leaving behind the humble mailpack. Now, market forces are making many marketers reconsider direct mail. Will you be one of those who pushes the envelope? 

John Watson is Chairman of WPN Chameleon

Business

How to maximise your virtual communications for effective team meetings

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By Tony Hughes, CEO at Huthwaite International leading global provider of sales, negotiation and communication skills development, shares advice on the key skills your team needs to create a great virtual communications culture.

Virtual meetings are now familiar territory. Despite this, many of us are unaware how to make them truly effective.

Understand the purpose

We’re all inundated with video call after video call, whether that’s for business meetings with colleagues or socialising with friends – it’s become a daily occurrence for most. If you had six or seven face-to-face meetings each day, you would quickly become overwhelmed, so consider this when planning virtual meetings too. Ensure each meeting has a purpose and make it clear to all involved from the start.  For example, is the purpose of the meeting to think creatively and generate new ideas or is your aim to get focused and make some important decisions in one or two major areas?  Make sure people know what is expected from them in advance.

Also, take into consideration who is attending each meeting. We’re all aware that communicating via video can lead to problems when there are too many people trying to have their say – so don’t overcomplicate it. On the other hand, you don’t want to create additional meetings to communicate the points already agreed so think carefully about who needs to be involved.   Base your decisions on your meeting invitations around the meeting purpose.

Engage people in a way that achieves your meeting purpose and manage your communication airtime

Our research into communication skills shows that there are three main classes of behaviour important to group interaction in task oriented situations, these are:

  • initiating behaviours– putting forward ideas, concepts, suggestions or courses of action
  • reacting behaviours– putting forward an evaluation of other people’s contributions
  • clarifying behaviours– exchanging information, facts, opinions for the benefit of the whole meeting.

Feedback on the proportions of these behaviours used in meetings can help groups examine their own behaviour and to assess the need for behaviour change. In effective group communications, all three main behaviour classes are present in a balanced way.

A tip to help set a good, cooperative tone for a virtual meeting and encourage a balance of behaviours is to start discussions with a non-controversial issue where people aren’t committed to a particular solution so a straight forward agreement can be reached, before diving into the more contentious areas of the agenda.   This encourages people to listen to and build on others’ ideas from the beginning, will help set the tone for the rest of meeting and will be a useful precedent to refer to. Try to structure meetings in a way that means all points are addressed properly and are fully developed before moving on to another issue or suggestion.

Don’t allow discussions to lead to a breakdown in communication

A strong indicator of an effective meeting is how well people respond to one another’s ideas and proposals. When a creative type meeting is working well, people react positively or at least constructively, to what others say. When a meeting is ineffective, the opposite occurs and tensions can rise leading to a potential communication breakdown which will diminish any successful meeting outcomes.

What we might perceive as a negative attitude can lead to what Huthwaite refer to as ‘Defend/Attack’ behaviour where opinions are expressed more strongly and more directly which can lead to people feeling exposed and becoming overly defensive. Defend/Attack usually involves value judgements and contains emotional overtones.

Avoid these behaviours by responding positively and appropriately and most of all, try to actively listen to what is being said. Really take the time to understand a differing point of view point and respect their position before jumping in with a response. Listening is key and our research shows it is often what separates skilled communicators from unskilled. Taking the time to listen will give you time and space to fully consider other opinions.  If you decide you do disagree with what they’re saying, actively listening will leave space around the discussion which offers the opportunity to react in a constructive, rather than an emotional manner.

Avoid irritating verbal behaviours

There are a few verbal behaviours that can be instantly harmful to meeting discussions and apply to meetings both in person and online. Virtual meetings can present multiple communication barriers such as poor connections and technology issues, leading to irritation for all parties involved so it’s important not to add further irritation with the words you choose. Declarations that you are being ‘fair’ and ‘reasonable’ when talking to people can cause tension as they can undermine the person you’re speaking to and may cause lasting damage to your relationship.

Other phrases, such as telling someone you’re ‘being honest with them’ or ‘that you’re trying to be frank’, can be very misleading.  You don’t intend to imply that weren’t being honest a moment ago but that is the inference you’re allowing by using these kinds of phrases.  Building a reputation that you are selectively honest is the kiss of death to a productive meeting.  Steer clear of this kind of language if you want to keep your reputation intact.

Make sure meeting standards don’t slip and build trust in your virtual environment

If you are hosting a business meeting online, it’s important that you don’t let your normal meeting standards slip. Try to nominate a meeting manager/chair who can focus on managing the discussion, making sure everyone speaks their turn and that you cover everything that needs to be discussed. Their purpose is to steer and guide the conversation in a productive manner. It’s helpful if the chair can clarify the information presented and the meeting outcomes, especially for long or heated discussions where meeting focus can shift about very easily.  This will ensure everyone is clear about what has been agreed.

Arguably, In an online meeting this can be done even more efficiently than in the real world. This is due to video conferencing features such as the ability to ‘highlight’ a particular participant when speaking or sharing links and additional information. So, if you want a meeting to be productive and efficient, use the rich features of the technology available to keep standards high and meetings effective.

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Business and data – building better operations

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By Bryan Kirschner, Vice President Strategy, DataStax

Building your business on data. What have we learned so far?

Coming into 2020, running your business based on what your data told you was a reality for some businesses, and a goal for many more. The coronavirus pandemic forced all companies to become more digital and more data-driven.

What lessons have we learned so far, and how can companies improve their data-driven processes over time?

There’s a meme going round about how the C-level term that has had the most impact on business and IT strategy in the past few years is not the CEO or CIO, but COVID-19. For some, this will lead to a chuckle at most. For others, it will ring all too true. In 2020, running your business based on what your data told you was a reality for some businesses, and a goal for many more. The pandemic forced all companies to become more digital and more data-driven.

For all businesses, data will continue to be essential to their operations. According to Rita Sallam of Gartner, the top ten trends for data through the rest of 2020 will be about scaling up and being more agile with data, as “… data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts.” COVID-19 has made this trend inevitable.

What comes next for data?

All companies are therefore becoming ‘data-driven’ companies. The challenge coming up is therefore how data can keep being a differentiator for businesses when every enterprise has access to data and analytics.

While companies can all gather data and use it for their operations, the real differentiator is speed. It’s not just that companies can generate and store data at scale, it’s that they can make decisions faster and then deploy data in valuable ways more quickly than their competitors. This plays into the affirmative side of competing against other companies as well – when markets are healthy and dynamic, new opportunities can emerge that you can take advantage of by moving more quickly.

Asking the right questions to get the right answers

Keep a customer focus in mind for your approach to data. By asking questions that focus on what customers need, you can get a head start in creating value that customers are willing to pay for. For example, asking how much your customers are willing to pay for your data products can quickly show you where you are – either you have a great product in place already that data can improve, or it will show you where you need to work harder around using data effectively.

Similarly, you can use data around your goals to improve your decisions. Asking what data your customers want around their interactions with you, and how you can provide them with insights from that data, can get you started. Alongside this, you can look at more strategic goals like how you can improve your Net Promoter Score over and above your competitors, how to reduce churn, or increase lifetime value, by supplying your customers with data products.

The wrong questions about data focus on internal and political issues. For example, if your team has to answer questions on how to prove the net present value of data over five years, or how to negotiate data access between business units, then your focus is not on the customer. There are other questions that are reasonable to ask – for example, around security of data and justification for storage costs – but these can easily distract you from the opportunities that exist around that data. Discussing these questions can easily lead your teams down rabbit holes.

You will likely be better off solving exactly the governance and security questions you need to in order to deliver one specific, new data-driven experience to customers in the next quarter, and then the next quarter after that, in turn, versus trying to solve them in the abstract. Because those new experiences will themselves generate data, if you ship faster, you will learn faster. This is a new way of working for many, but getting this flywheel spinning is the key to staying ahead if you’re starting ahead–or stealing a march on competitors who don’t realize its importance.

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What Skills Does a Data Scientist Need?

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What Skills Does a Data Scientist Need? 3

In this modern and complicated time of economy, Big data is nothing without the professionals who turn cutting-edge technology into actionable insights. These professionals are called Data Scientists. Modern businesses are awash with data and many organizations are opening up their doors to big data and unlocking its power that increases the value of data scientists. Data is one of the most important features of any organization which helps to make decisions based on facts, stats, and trends.

As the scope of data is growing, data science came up as a multidisciplinary field. Data science is an integral part of understanding the working of many industries, complex or intricate. It helps organizations and brands to understand their customers in a much better, enhanced, and empowered way. Data science can be helpful in finding insights for sectors like travel, healthcare, and education among others. Its importance is increased as it solves complex problems through Big Data. With data science, companies are using data in a comprehensive manner to target an audience by creating better brand connections. Nowadays data science is taking an important and big prime role in the growth process of brands, as it is opening new fields in terms of research and experiments.

Let us know about the much-hyped role of a data scientist, the skills required to become one, and the need to take data science training.

Who is a Data Scientist?

Data Scientists are the individuals who gather and analyze large sets of structured and unstructured data. It combines the roles of computer science, mathematics, and statistics to create actionable plans for companies and other organizations. They gather, analyze, and process the data and then find the filtered results. Their work is to make sense of large, messy, and unstructured data using sources such as social media, smart devices, digital channels, emails, etc.

In other words, data scientists are analytical data experts who solve complex problems through technical skills to explore what problems need to be solved with available data. They are struggling with data all the time and experimenting via complex mathematics and statistical analysis. Usually, data scientists are required to use advanced analytics technologies such as machine learning, advanced computing, and predictive modeling. They use various types of reporting tools and analytical skills to detect problems, patterns, trends, and connections between data sets. Their goal is to provide reliable information about campaigns and consumers that help companies to attract and engage their customers and grow the sales.

A job of a data scientist is also known and advertised as a machine learning architect or data strategy architect. Data scientists generally require enough educational and experiential background of big data platforms, tools including Hadoop, Pig, Hive, Spark, and MapReduce and programming languages such as SQL, Python, Scala, and Pearl; and computing languages like R.

Skills Needed To Become a Data Scientist

To become a data scientist, it is recommended to have a master’s degree. This means a very strong educational background and the deep knowledge is must-required to become a data scientist. You must have a bachelor’s degree in any stream such as computer science, Physical science, social science, statistics, and mathematics or engineering.

The skills required to become a data scientist are categorized into technical and non-technical. Some of them are mentioned below:

Technical Skills

● R Programming

R is specially designed for data science to deal with big data. It is generally preferred for data science to gain in-depth knowledge of analytical tools. Almost 43% of data scientists are using R to solve data problems and statistical issues.

● Python Coding

The most required technical skill to become a data scientist is having the knowledge of the most common coding language that is Python along with C, C++, Java, and Pearl.

● Hadoop Platform

It is the second most important skill to be a data scientist. This platform is heavily used in several cases. Hadoop is used to convey the data quickly to different servers.

● Apache Spark

It is becoming the most popular big data technology in the whole world. Just like Hadoop, it is a big data computation framework, but it is faster.

● SQL Database/Coding

With SQL database and coding, data scientists are able to write and execute complex queries in SQL.

● Data Visualization

A data scientist can visualize the data with data visualization with tools such as ggplot, d3.js and Matplottlib, and Tableau.

● Machine Learning and AI

Machine learning techniques include reinforcement learning, neural networks, adversarial learnings, etc. Along with it, supervised machine learning, decision trees, logistic regression can help you stay ahead from other data scientists.

Non-Technical Skills

There are also some non-technical skills such as Intellectual curiosity, Communication skills, Business acumen, Teamwork, etc. that can make you a successful data scientist.

Ready to Learn Data Science?

Data Science is nowadays a buzzing word in the IT sector. It has become an evolutionary technology that everyone is talking about. Several people want to become data scientists. It is a versatile career that is used in many sectors such as health-care, banking, e-commerce industries, consultancy services, etc. This career is one of the most highly paid careers. Data science careers have been always in high demand so the seekers have numerous opportunities to start or boost their careers.

It is a widely abundant field and has vast career opportunities because there are very few people who have the required certifications and skill-set to become a complete data scientist. You can gain these skills by enrolling in an online data science training program. By learning from industry experts, you will have a strong foundation of data science concepts. You’ll also be able to work on different data science tools and industry projects through a training course. So it’s the right time to get certification and grab the golden opportunities in the Data Science career.

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