From an operations standpoint, standardization can seem like the easiest method for expansion, using the same marketing and customer experience style and theme for all your products and services, regardless of the region in which you’re trying to sell them.

However, localization is often more effective, as it allows you to fit in with your new target market’s specific needs by making linguistic and physical adjustments to your existing products and services.

Done correctly, it should decrease barriers to entry, provide customized local customer experience, breed cultural respect and lead to better brand identification, and hasten local business development.

Where should you start when planning your localization strategy?

As with everything in life and business, the key to getting your localization strategy off the ground in the most efficient way possible is research, research, and more research.

Start with a deep dive into your analytics to gain a better understanding of your customers’ preferences and how they might vary from place to place.

Accurate localization means much more than just translating product descriptions into local languages, and there are many essential elements to consider before embarking on such a venture.

Your localization strategy is what will set you apart from companies that merely operate in multiple countries, establishing your business as one that has thriving and long-lasting growth in all your target markets.

Step One: Find out who your customers are.

If you’re looking at a map for directions, it’s essential to find yourself before looking for your final destination and start to plan how you’re going to reach it.

Use a combination of customer surveys and web analytics to find out who your existing customers are, what languages they speak, and other factors that might influence their buying choices, from culture to purchasing power and average income.

Begin by studying potential international customers and try to put yourself in their mindset. What do you have to offer that fits their specific needs, and what are the best ways to reach them? How will that differ from the way you serve your current customers?

Step Two: Decide which market(s) you want to target next.

Based on the information you’ve collated about your current and potential customers; you now have to decide which markets make the most sense for your business to expand into next.

You may want to carry out some trial runs in a few different markets to test the waters, move into one new market at a time, or go worldwide all at once. This medium will be very much dependent on your product, your ultimate goals, and your specific customer base.

Step Three: Research your new market(s).

Start by looking at how your new market differs from the one(s) you already serve. Look at market conditions, in-demand products, typical purchasing power and income, barriers to entry, and local laws and regulations.

Remember that while local markets may be saturated with competitors, that shouldn’t necessarily be a barrier to entry for your business. A large amount of competition can signal that a market is very healthy and ripe for new entrants.

Do some market research ahead of time to help identify culturally relevant features that your competitors might have that will resonate with your target market, set your product apart, and ensure that your future customers gravitate towards your business, not the competition.

Step Four: Define your project goals.

Now that you have a clearer picture of who your new customers might be, where you’re going to find them, and what the local market looks like, it’s time to figure out precisely what it is that you want to get out of this expansion.

What are your specific goals for this project? What are you hoping to achieve? It’s not just about determining how many new markets you want to enter and how many new customers you want to add through that expansion.

Consider the little things as well: how many languages do you want to work with? What marketing strategies do you want to use? How long should the whole process take? How many new employees or freelancers will you need? What is your total budget for the project?

Step Five: Sweat the details.

The main goal of localization is to adapt your business to a new market, so there are a ton of factors that you’ll need to take into consideration. Start with the culture and language of the customers you’re trying to reach.

Local expertise

Consider employing local experts. Who knows a culture better than the local people? Look into and talk to local staff, agencies, and even in-country partners in your target market(s). Don’t forget about the “local” in localized.

Make sure that you have a presence in your new market – in a sense; you want to become “part of the community.” Stay aware of local events and issues, and seek out moments of importance where you can connect with and give back to the local people.

Run market research studies and focus groups – and take the feedback that you receive very seriously. This process will ensure that you understand the dynamics of the local market, customers’ preferences, your competitors, and available marketing channels, before anything else.

Translation

While languages aren’t the be-all and end-all of the localization, being understood in your target market is essential to accessibility, conversion, and – ultimately –sales.

Reportedly, 42 percent of Europeans only shop online in their native language, and 72 percent of online shoppers who aren’t native English speakers would like product reviews to be available in their native language.

You’re going to want to translate your marketing materials and product descriptions into the local language(s), as well as making them culturally relevant. Advertisements that work well in London may not be so easily understood in Tokyo or Paris, even when translated into Japanese and French.

Again, you’re going to want to think about going to the locals for this one, since unintended nuance and cultural differences can lead to misunderstandings and confusion that you never even saw coming, but that a native speaker would spot from miles away.

Money issues

Find out what currency your new market trades in and which payment methods are most popular, and consider pricing strategies. What do similar products cost in your new market, and how much can your new customers afford to pay? How much are they willing to pay?

Learn about relevant local laws and tax regulations. One of the main steps in localization is making sure that you can make your product physically available in a new market. Are their inhibitive customs or tax laws in play, either on your end or theirs?

You might want to consider setting up in-country distribution centers or even employing local manufacturers so that you don’t have to ship anything in and out of the country. In some areas of the world, there may also be marketing restrictions that you’ll need to consider – for instance, Facebook marketing is useless in China.

Design

Choose culturally relevant images, and consider how customers in each market will experience your brand. Find out what customers in each market already think of when they see your company name or logo.

You may very well find that your brand is received differently in different markets and that you will have to work harder to create a new, memorable story for your business in some countries than others. Specific colors may be received differently, and even the name of your brand might have an unintended meaning in some languages.

Digital presence

Finally, think about website design, mobile optimization, and your social media presence. The way that a business presents itself online can be a crucial element in how it is perceived by customers today.

Creating localized content for apps can be of particular importance as it presents a unique opportunity for growth. Having individual apps for each location can vastly increase conversions in those markets.

Look into social networking trends in your target markets, as platforms such as Twitter and Instagram are accessible on a global scale, and are often the primary location in which you will directly interact with your customers.

Different regions and demographics will prioritize different platforms, and localized content in multiple languages is an essential part of any new marketing strategy.

Localization 101 – Do your research and plan ahead

If you’re thinking of taking your business global, localization is the key to a successful launch. And the key to efficient localization is to do your research and make sure that you have a plan.

Before you decide where you want to go, make sure that you know where you are already. Then, look into new customers and new markets through studies and intensive, focused research. Choose the most appropriate markets for your business to target and get planning.

Find out about local cultural norms and differences, and learn how your business might successfully assimilate. Define your goals for the expansion, focusing first on the big picture, and then on individual, measurable milestones that will get you where you want to go.

The post Going Global? Five necessary localization steps you need to get right. appeared first on Ekitai Solutions.

Sometimes it seems like the internet is virtually awash in discussions about artificial intelligence, machine learning, and other technologies potentially replacing humans in the workplace.

A robot reporter used by The Washington Post published 850 articles in its first year in action, and Associated Press, a non-profit newswire based in New York City, has started automating some men basketball coverage and quarterly earnings reports using artificial intelligence.

Some journalists have even started to worry that their jobs could be replaced by robot reporters, a feat that would have seemed unthinkable – if not impossible –just a few years ago. The language or translation industries are no different in this regard.

However, it’s unlikely that artificial intelligence-powered translators will be replacing human translators any time soon. Some experts even think that the technology itself is already being over-hyped.

What does it mean?

Simply put, artificial intelligence-aided or machine translation automatically converts text from the source language to text in the output language without the need for a human translator. Theoretically, artificial intelligence can learn more languages than a human, and translate between them at a much faster speed.

There are several different types of machine translation programs that a business can use. The most common are statistical machine translation (SMT-based) – such as Google Translate – and rule-based machine translation (RMBT-based).

The SMT-based translation uses the concept of probabilities to refer to a set of target segments, then chooses the most likely words or phrases as a match to the source segment. I.E., it translates by finding the highest statistical probabilities that a translation is correct.

Conversely, RMBT-based translation operates on the basis that language is all about syntax and grammar rules. Such programs refer to bilingual dictionaries for the specified languages that they are required to translate between.

These dictionaries are made up of linguistic rules that apply to the structure of sentences in each language, and rules to help the program link the sentence structure of each language to each other.

However, the process is time-consuming as new requirements have to be met each time a new language is paired with the source language.

It’s very effective when translating between languages with very different word orders, such as English and Chinese. But, it depends on a much more extensive list of sources that SMT-based programs, which can accommodate a much wider array of languages.

Google’s artificial intelligence-translator can now translate your speech while keeping your voice, according to the MIT Technology Review, after researchers trained a neural network to map audio “voice-prints” from one language to another.

The results aren’t perfect, but the translator was able to keep the voice and tone of the original speaker by converting audio input directly to the audio output without intermediary steps. More traditional systems would typically convert audio into text, translate the text, and then re-synthesize the audio, losing the characteristics of the original voice and tone in the process.

So is it possible that machine translators could replace humans in the workplace?

Artificial intelligence is ubiquitous today. Among other uses, it powers virtual assistants, such as Amazon’s Alexa and Apple’s Siri. It can recognize who and what is in a photo. It has ideas about what you should buy next when you’re shopping online, based on preferences and previous purchases.

There are two broad types of artificial intelligence: narrow and general. The former are intelligent systems that have been taught or have learned how to carry out tasks without specific programming. It has many emerging applications, such as interpreting video feeds from drones, organizing calendars, and helping radiologists spot tumors on x-rays.

General artificial intelligence is more theoretical. It doesn’t exist today but can be found in science-fiction, represented by the likes of Data in Star Trek, HAL in 2001: a Space Odyssey, and Skynet in the Terminator franchise.

It is the kind of intellect possessed by humans – a truly artificial consciousness – and would be capable of learning how to carry out a wide variety of tasks or reason about a wide range of topics based on accumulated experience.

This would be the kind of artificial intelligence translator that would have the ability to replace human translators in the workplace. Current machine translators are narrow artificial intelligence. They are capable of “learning” languages, but they cannot fully appreciate the nuance inherent in human communications.

Machines can’t understand the culture (yet)

Different cultures have different lexical items – like slang, idioms, and proper nouns – that are unique to that specific culture. Machines don’t yet have the complexity to understand or recognize them.

Meanwhile, native speakers who are well versed in the languages into which they are translating, and understand all the slang and idioms of the respective countries, are usually skilled enough to find appropriate equivalents.

Sometimes, a word can mean one thing in one culture, and something totally different in another. Context is important in translation and often completely dependent on human involvement as machine translators can only perform direct word to word translation.

In other words, just because they can translate a word directly, that doesn’t mean that they understand it’s meaning, which can completely alter the translation itself. Similarly, many languages have words with dual meanings, which can be a problem for machine translators.

Languages are, almost by definition, subjective. Artificial intelligence, on the other hand, typically excels at tasks that are rooted in objective reality, functioning best when confronted with clear mathematical or physical rules that govern their decision-making.

However, languages are subjective constructs invented by groups of humans to communicate with each other. While they often exhibit rule-like behavior, this is grounded in the convention, not objective reality, and continuously evolving.

Robots don’t do humor.

Even human translators find jokes, puns, nuanced cultural references, and the occasional bit of sly innuendo hard to get right. Different cultures find different things funny, and differences in spelling and vocabulary can render clever wordplay meaningless.

From an interpreter’s standpoint, tone of voice and body language also directly inform a speaker’s intent and have to be accurately analyzed and conveyed in the target language too. This is challenging for humans and – so far – impossible for a machine.

A move from statistical, phrase-based machine translation to neural networks has resulted in significant improvements in overall quality. But, neural machine translation is now even more dependent on huge sets of training data than previous models.

And since the most significant bilingual data sets available often come from official translations of government documents and religious texts, these algorithms have pitifully low exposure to humor, wordplay, and non-verbal expression.

Furthermore, machine translators can’t admit to – or correct – their mistakes. When Google Translate started offering biblical prophesies in exchange for junk input, for example, experts attributed the errors to neural networks’ preference for fluency over accuracy.

These “false positives” are far more problematic than more obvious mistakes, as audiences in the target language might not realize that a glitch has occurred and could attribute the outlandishness of the translation to the original text itself.

Machines can’t translate on the fly

The above challenges make it difficult enough to perform machine translation on the static text. Asking a computer to translate live speech simultaneously adds several extra layers of complexity, including automatic speech recognition (ASR).

When you have a conversation with Siri or Alexa, they seem to be pretty competent conversationalists, but that exchange is still constrained within a narrow set of context and conditions; short, command-based interactions with a finite vocabulary in a controlled environment.

Most situations in which real-time translation of live speech would be required – such as conferences and business discussions – however, feature speech that is spontaneous, continuous, and often highly dependent on context and specialist knowledge.

Perhaps unsurprisingly, these are traits that send the error rate of most ASR programs soaring. For example, during a speech given by hedge fund guru Ray Dalio, in which he reflected on his mis-forecasts as a young trader, a real-time subtitling machine translator rendered “How could I be so arrogant?” as “Aragon, I looked at myself and I.”

Recent advances in the field have shown some promise. Many experts predict that the word error rate of ASR software will reach parity with human transcribers soon. However, not all word choice errors are equal and won’t always be relatively inconsequential.

Machines aren’t coming for your job (yet)

All of this is to say that it seems unlikely that machine translators will be replacing their human counterparts tomorrow.

While translators and interpreters – alongside copywriters, journalists, and other language economy professionals – may very well lose their jobs to robots at some point in the future, this isn’t going to happen tomorrow.

However, some experts estimate that within the next one to three years, and machine translators will be taking on around 80 percent of corporate translation work.

This doesn’t mean that organizations like the United Nations and police forces won’t need translators, or that we won’t still need sign language interpreters. It is more likely that machine translators will increasingly become just another tool in the arsenal of a good translator.

Computer-assisted translation tools are already widely used among text translators, and while some may object to the idea, simultaneous interpreters could almost certainly benefit from a combination of speech recognition and translation memory technology.

For translators looking to machine-proof their careers – as best as possible – it might be wise to specialize in those languages that are less widely spoken, and encourage the industry to see artificial intelligence as a complement to human output, not a replacement.

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