As a Finance AVP Tampines, its very critical for you to understand developing brand strategy is extremely critical. The most important asset your company has is its brand. Quite simply, it drives the direction of your business. So you should definitely have a well thought out brand strategy in place.
Increasing competition in business develops similar products with good quality from different manufacturers. But only an effective, innovative and Marketing Strategy & planning can make your business and products more popular.
For your profession as Finance AVP Tampines it becomes your responsibility to stay connected with like-minded supporting industry experts who can guide and help you deal with your day to day work issues.
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If you are entrepreneurial in nature owning a business is very exciting adventure. It can also be the most difficult thing for you to get into if you are not prepared.
What is it that makes some brands connect so well with their audiences? We could learn something about building brands for organizations by also asking, What is it that makes some people connect so well with other people? In many ways, organizations are like individuals. Each has its own specific "fingerprint" -- strengths, character, and personality -- that makes it unique and recognizable. It's how we get to know our friends and understand what it is about them that we like. In a world where no one has time to carefully weigh all available brand options, this fingerprint acts as shorthand to help us sort through the maze, a very real point of value at a time when it is increasingly difficult to tell one product or service from another. When an organization's brand fingerprint is clearly defined and articulated so that customers, shareholders, distributors, employees, and partners consistently feel they "know" the organization and know what to expect from it, magic happens.
This is when high emotional engagement occurs. This is when "raving fans" and customer loyalty are created. This is when organizations gain sustainable competitive advantage. Discovering and communicating this brand fingerprint helps organizations bring strategic focus to the power of their brand -- giving brands a meaningful and recognizable shorthand that helps cut through the noise and clutter to connect with people.
Brand fingerprint process
Following a process to help uncover the organization's brand fingerprint will ensure that the intangible attributes assigned to the brand -- assets like integrity and innovation -- are translated into a visual, tangible representation to which audiences can relate. The process has two phases, strategy and visual translation. It works like this:
Phase I. Strategy
Step 1. Finding your brand values, character, and personality
Step 2. Understanding the competitive landscape
Step 3. Determining your position in the marketplace
Step 4. Developing your value proposition
Phase II. Visual Translation
Step 1. Developing the brand mood
Step 2. Determining the key brand elements
Step 3. Developing the brand roadmap
Phase I. Strategy
The strategy phase can be compared to traditional methods of brand development and is based on core values. The difference here is that the exercises used in the facilitated sessions with company decision makers are designed not only to uncover brand values and attributes, but to gather information in a way that it will be useful for development of the visual translation of the brand. Pairing the creative team with decision makers at the very beginning of brand strategy development is essential in gathering input that will be critical to visual translation.
This is important since experts say that 80% of what we learn comes to us visually, and customers will most likely see brands long before they understand the strategy. There are many benefits of considering how the brand will be communicated visually at the strategy stage. Some of these benefits include: - translation of intangible company assets and attributes into tangible representations that truly reflect the company's core values - avoidance of possible disconnects when logos, websites, and print materials are developed - development of marketing materials that really communicate key messages - deeper understanding and long-term recall of brand messages by customer audiences - consistency of brand messages over time
Phase II: Visual Translation
The visual translation phase takes all of the information gathered in the strategy phase and translates it into a visual form that people can see and relate to -- the visible brand fingerprint. A clear and accurate brand fingerprint can communicate assets like integrity, zero defects, and innovation and make them palpable. Visible. Understandable. Audiences will know at a glance "who" the organization is, what it is saying to them, and why they should buy, react, or be moved. And it will be real, it will be authentic, and it will stand the test of time -- because what people see represents the synthesis of the brand strategy.
The benefits of developing the visual components of the brand directly from strategy exercises include:
- a brand mood that will communicate to customers on an emotional level, because the design is based on authentic aspects of the brand's character and personality - because the mood is a direct translation of strategy jointly developed by company decision makers and creative team, there are no unpleasant surprises at the design stage - the main visual components of the brand will look and feel "real" and will become the pillars upon which other marketing materials will be built - there will be no need for new themes, visual approaches, or deviations from the established visual translation. Brand equity builds with consistency. This is a cost-effective benefit.
Being true to the organization's authentic brand is how trust, loyalty, and sustainable relationships are developed between the organization and its audiences. Great graphics and cool animation aren't effective if they don't accurately communicate the company's character or brand. Something's amiss if the organization is not clear and consistent about how it is presenting itself in front of its publics. If the organization's brand and its image are not aligned, "brand schizophrenia" occurs, which significantly affects the quality of the relationship and level of trust with valued audiences, including customers and employees. Both lose trust in companies when they don't know what to expect. With brand strategy and visuals clearly articulated in a unique brand "fingerprint," organizations can make a real connection with their audiences. Once established, this connection enables them to communicate compelling value, promote long-term recall of brand messages, and foster the trust, loyalty, and emotional attachment that sustain relationships.
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With the support of our professional business network, you get the opportunity to exchange experience and knowledge at a top professional level, and to strengthen and develop your own skills within your management and specialist areas.
Through business relationships and experience sharing in confidential settings for Finance AVP Tampines, we strive to create personal and business value for all our network peers.
Hollywood paints a grim picture of a future populated by intelligent machines. Terminator; A Space Odyssey, The Matrix and countless other films show us that machines are angry, they’re evil and, if given the opportunity, they will not hesitate to overthrow the human race. Films like these serve as cautionary tales about what could happen if machines gain consciousness (or some semblance of). But in order for that to happen humans need to teach machines to think for themselves. This may sound like science fiction but it’s an actual discipline known as machine learning.
Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.
For digital marketers, machine learning may be especially helpful in getting products or services in front of the right prospects, rather than blanket-marketing to everyone and adding to the constant noise that is modern advertising. Machine learning will also be key to predicting customer churn and attribution: two thorns in many digital marketers’ sides.
Despite machine learning’s positive impact on the digital marketing field, there are questions about job security and ethics that cannot be swept under the rug. Will marketing become so automated that professional marketers become obsolete? Is there potential for machine learning systems to do harm, whether by targeting vulnerable prospects or manipulating people’s emotions?
These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.
What is Machine Learning?
You can think of machine learning as using a computer or mathematics to make predictions or see patterns in data. At the end of the day, you’re really just trying to either predict something or see patterns, and then you’re just using the fact that a computer is really fast at calculating.
You may not know it, but you likely interact with machine learning systems on a daily basis. Have you ever been sucked into a Netflix wormhole prompted by recommended titles? Or used Facebook’s facial recognition tool when uploading and tagging an image? These are both examples of machine learning in action. They use the data you input (by rating shows, tagging friends, etc.) to produce better and more accurate suggestions over time.
Other examples of machine learning include spell check, spam filtering even internet dating - yes, machine learning has made its way into the love lives of many, matching up singles using complicated algorithms that take into consideration personality traits and interests.
How Machine Learning Works?
While it may seem like witchcraft to the layperson, running in the background of every machine learning system we encounter is a human-built machine that would have gone through countless iterations to develop.
Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.
So how exactly does machine learning work? Spoiler alert: it’s complicated. So without going into too much detail, here’s an introduction to machine learning, starting with the two basic techniques.
Supervised learning systems rely upon humans to label the incoming data - at least to begin with - in order for the systems to better predict how to classify future input data. Gmail’s spam filter is a great example of this. When you label incoming mail as either spam or not spam, you’re not only cleaning up your inbox, you’re also training Gmail’s filter (a machine learning system) to identify what you consider to be spam (or not spam) in the future.
According to Tommy, this type of machine learning can be likened to the relationship between a parent and a young child. When a child does something positive they’re rewarded. Likewise, when “[a machine] gets it right - like it makes a good prediction - you kind of give it a little pat on the back and you say good job.”Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.
Unsupervised learning systems use unlabeled incoming data, which is then organized into clusters based on similarities and differences in the data. Whereas supervised learning relies upon environmental feedback, unsupervised learning has no environmental feedback.
The Power of Machine Learning
A lot of what machine learning can do is yet to be explored, but the main benefit is its ability to wade through and sort data far more quickly and efficiently than any human could, no matter how clever. Tommy is currently experimenting with an unsupervised learning system that clusters landing pages with similar features. Whereas one person could go through a few hundred pages in a day, this model can run through 300,000 pages in 20 minutes.
Machine Learning and the Digital Marketer
As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data. This process usually involves hours of digging through analytics, collecting data points from marketing campaigns that span several months. And while focusing on data analysis and post-mortems is incredibly valuable, doing so takes a significant amount of time and resources away from future marketing initiatives.
As advancements in technology scale exponentially, the divide between teams that do and those that don’t will become more apparent. Those that don’t evolve will stumble and those that embrace data will grow — this is where machine learning can help.
That being said, machine learning isn’t something digital marketers can implement themselves after reading a quick tutorial. It’s more comparable to having a Ferrari in your driveway when you don’t know how to drive standard or maybe you can’t even drive at all.
Until the day when implementing a machine learning system is just a YouTube video away, digital marketers could benefit from keeping a close eye on the companies that are incorporating machine learning into their products, and assessing whether they can help with their department’s pain points. So how are marketers currently implementing machine learning to make decisions based on data rather than gut instinct? There are many many new niches in marketing that are becoming more automated.
Networking has always been considered a powerful tool for improving business prospects, advancing a career, and developing ideas. Other than some brief, structured events, networking has been mostly informal and inexpensive in comparison to cost they otherwise spend on different channels. But membership is growing in many formal, long-term networking groups, and so is the price tag.
Our groups are not groups for generating sales leads, nor are they places where individuals can drop-in to gain quick advice on an immediate challenge. Members also sign a confidentiality agreement and benefits from the guided mentoring to help each other.
These groups include an experienced facilitator and use a structured discussion method to ensure appropriate participation.