Eatoni's
LetterWise: the linguistic argument
This document shows a simple way for a phone manufacturer to
- Allow over 100 million new customers to communicate quickly by
text messaging in their native language.
- Reduce the memory requirement of phones.
- Reduce the costs and risks associated with phone production,
inventory and distribution.
- Make products simpler and easier to use.
- Catch the eye of the press through innovation.
| Predictive text entry on mobile phones |
Virtually every phone manufacturer offers some form of predictive
text-entry system on their mobile phones. The most widely used system
is T9, produced by AOL. Others include iTap (Motorola), and eZiText
(Zi Corporation). All these methods require the phone manufacturer to
install a large dictionary of words for every input language in their
phones. Dictionary-based systems frequently fail. When this happens,
users must fall back on using a laborious and slow secondary system,
known as Multi-Tap.
| Product differentiation in a market driven by replacement sales |
The cell phone market is increasingly driven by replacement sales. In
2001, over 50% of sales were replacements. That figure is projected
to rise to 75% by the end of 2002. Manufacturers must confront the
fact that replacement customers are more discerning in their
purchasing and need to see clear reasons to select a new phone. They
will use experience to make decisions based on comparison of available
features. As a result, phone manufacturers have to work harder to
differentiate their product. Thus there has been a rapid proliferation
of new (non-functional) features such as games, downloadable ring
tones, changeable face plates, etc. In the midst of this activity and
the flurry of increasingly exotic features, a fundamental user need
has been ignored: giving people the option of rapidly and easily
sending text messages in their preferred language.
Eatoni Ergonomics has developed LetterWise, an easy-to-use predictive
text entry system currently being introduced into GSM, CDMA, and DECT
phones as well as other devices that use a reduced keypad for text
entry. The principle objectives driving the development of LetterWise
were to provide high-quality predictive text entry and simplicity in
user interface, using minimal memory. Unlike other systems, LetterWise
does not use a dictionary and never requires the use of Multi-Tap.
LetterWise is available today in over forty languages.
LetterWise makes it possible for a manufacturer to stand out in a new
and important way: by providing rapid text entry to people who speak a
language other than the dominant one in a region. The aggregate
numbers involved are enormous. There is the potential for
manufacturers to increase sales by millions of units and to increase
brand loyalty, and for carriers to reduce churn and increase ARPU as
new and repeat customers significantly increase their use of text
messaging.
In this document we measure the scale of this opportunity, explain
why it exists, and show why Eatoni's LetterWise solution is uniquely
positioned to take advantage of it.
Eatoni has done extensive linguistic research during the development
of software for text entry in 120 languages. Our linguistic database
contains detailed information on the numbers of speakers of 7,000
languages in 260 countries, on cell phone penetration by country, on
country population, on predictive text entry language availability by
software supplier, by phone manufacturer sales and by country.
By combining information from linguistic research sites such as
Ethnologue, and from sources such as the CIA World Factbook,
government census figures, analyst research reports, numerous
manufacturer phone manuals, corporate web sites, news reports and
press releases, Eatoni is uniquely positioned to provide detailed
analysis of global linguistic demand and to produce manufacturer- and
operator-specific reports.
| Unsatisfied linguistic demand |
There are three gaping holes in support for predictive text
entry in today's market:
-
Ignored foreign linguistic minority: Imagine yourself as
a Norwegian speaker living in New York (there are 612,000 Norwegian
speakers in the U.S.). You have a number of Norwegian friends in
your neighborhood, and you have many friends and relatives back in
Norway. You would like to send text messages in Norwegian, but it is
not included in the languages provided by your U.S.-bought
mobile phone. Furthermore, you are unable to find any phone for sale
in New York that offers Norwegian as a language for predictive text
entry. You friends have a similar complaint and you all use the
laborious Multi-Tap method to send messages in Norwegian to each other and
to family in Norway.
-
Ignored national minority language: Or, imagine you are
Welsh, and that although you speak fluent English, you are also one of
the 500,000 speakers of Welsh. All your friends speak Welsh and you
all use Multi-Tap to send each other messages in Welsh. You would
happily use predictive text entry in Welsh and would also like to be
able to use Welsh words in your English text messages. But, T9 does
not allow you to freely mix words from other languages in a single
message, and of course Welsh is not available in your phone in the
first place.
-
Ignored country: Finally, suppose you are Icelandic,
and live in Iceland, the country with the world's highest cell phone
penetration. Predictive text entry with T9 or eZiText in Icelandic is
not available. Why not? Because there are only 250,000 people in
Iceland. Including Icelandic in a phone destined for the Northern
European market at the expense of a language for the far more populous
other countries of the region makes no sense. Phone manufacturers are
sending a clear message to their customers in Iceland: You do not
matter. One can only imagine the reception of a phone on the Icelandic
market that offered high quality predictive text entry for SMS in
Icelandic.
These people have something in common: their preferred language is
either not available in phones in the region where they live, and, in
many cases, has never been available in any phone anywhere. Their
joint predicament is an opportunity for phone manufacturers.
How many of these people are there? What languages do they speak?
Where do they live? Eatoni's research answers these questions.
Eatoni's LetterWise is the key to delivering a differentiated and
attractive product to these people.
| Aggregate linguistic impact |
LetterWise makes it possible to offer predictive text entry using just
3K bytes per language. It is probable that phones will appear on the
market offering 50, 100, or even more languages. The Panasonic
KX-TCD755 DECT phone, which uses LetterWise, has 24 languages
installed.
We will now examine the aggregate linguistic market for such phones. A
couple of examples have already been mentioned: 612,000 Norwegian
speakers in the U.S. and half a million Welsh speakers in the
U.K. These are relatively small numbers. The interesting question is:
What does the picture look like when we consider all the languages in
all the countries in Europe, Asia or the Americas?
Imagine the following experiment. A cell phone manufacturing company
sends their market research team to question every person in every
country in Europe. Interviewees are asked to list the languages they
speak. For each language a person speaks that is not available on any
phone that can be purchased locally, the interviewer adds one to the
total for that language. At the end of this process, the researchers
pool their results across all countries and languages.
Assume that before the market research begins, the phone manufacturer
has divided Europe into four regions (North, South, East, West) and
distributed phones with five T9 languages as follows:
| Region | Languages |
| North | Danish, Dutch, Finnish, French, German |
| South | English, French, Greek, Italian, Spanish |
| East | Bulgarian, Hungarian, Romanian, Russian, Slovak |
| West | Dutch, English, French, German, Portuguese |
Given this distribution, what would the market study show? Eatoni's
research indicates that:
- The sum of the interviewer's counts across all unsupported
languages is 210 million.
- Therefore, if people in Europe speak an average of two languages
each, there is a market opportunity to address the needs of over
100 million people.
- A total of 74 different languages would be found to be
unsupported, counting only those languages with at least 100,000
speakers.
The conclusion of the study is clear: a very large number of people
are being denied a basic need by the company's current linguistic
policy. How can a manufacturer turn these people into customers?
| Dictionary-based systems cannot address this opportunity. Actually, they create it. |
Although interesting as individual stories, markets such as the
200,000 Turkish speakers in The Netherlands have until now been too
small for manufacturers to address. The main reason for this is that
T9, the dictionary-based predictive text entry software available from
AOL, uses approximately 60K of memory for each language dictionary,
and over 100K for some languages. To provide even five languages in a
phone, manufacturers have been forced to dedicate over 300K of memory
per phone. As memory is both limited and expensive, including T9 and
one or more languages has a very significant cost, both in terms of
money paid for memory and in terms of lost opportunity. Opportunities
are lost because the existing memory could have been used to provide
other features (additional games, larger address book, storage of more
SMS messages, longer voice memos, screen savers, etc.).
Thus the choice of which T9 languages to include in a new phone has
been a serious problem for manufacturers. Omitting languages means
ignoring the linguistic needs of millions of potential customers,
while including languages rapidly consumes memory and thus greatly
limits other functionality. As phones have begun to incorporate more
memory intensive applications, such as WAP browsers, the competition
for scarce phone memory has intensified. With the white hot pressure
to reduce phone costs in order to survive as a manufacturer, the
answer is not to install larger quantities of expensive memory.
Memory intensive dictionary-based predictive text solutions limit the
ability of manufacturers to appeal to a wider market. Manufacturers
must resort to dividing their markets geographically, offering
different small subsets of languages in each. Manufacturers deliver
embarrassing and awkward solutions that offer phone menus in over
thirty languages, but predictive text software in just a subset of
these. As a result, customers have to puzzle over setting their "phone
language" versus their "Tegic language". The situation is made worse
by the need for users to resort to Multi-Tap to enter names into their
address book because the dictionary-based methods are useless for
generalized entry of names.
In these ways, the use of memory-intensive dictionary-based predictive
text solutions forces the manufacturer's hand. With a product such as
T9 or eZiText, even if the needed language databases were available,
there is simply no way to make phones appeal to a wider linguistic
audience without dedicating megabytes of memory to store these
databases. Manufacturers who use these products are forced to draw
gross linguistic and geographical divisions that necessarily allow the
needs of hundreds of millions of people to fall through the cracks.
| Using Eatoni's LetterWise to tap the linguistic opportunity |
Fortunately, there is a quick solution to this dilemma
- Put predictive text in 80 languages into every phone.
- Do not divide up the market linguistically and geographically:
address it all at once, with every phone.
LetterWise makes this simple solution possible. LetterWise is
currently available in 120 languages. With its extremely
modest per-language memory requirement, a manufacturer can today
produce a phone with 50 languages, using just half the memory that T9
or eZiText would use for only 5 languages. Only with LetterWise can a
manufacturer simultaneously address the broad linguistic needs
described above. This a the key difference that LetterWise
provides. Minority linguistic communities can be addressed without
sacrificing support for larger ones. As we've shown, these minority
communities frequently number in the millions and sometimes comprise
entire countries.
| Why is predictive text entry so important? |
The availability of predictive text entry drives increased SMS usage.
For this reason, predictive text is important to ordinary phone users
and also to the phone carriers whose revenue is increasingly buoyed by
the rise of SMS and other data traffic. Ease of messaging implies
increased messaging. Ease of phone use increases brand loyalty. In
addition, the ability to rapidly enter product names, song titles,
search strings, email addresses etc., with minimal difficulty will
also be a important component complementing applications provided
through Java, WAP and other interfaces. In short, predictive text
entry on reduced keyboards will become part of the expected framework
in which people will operate their phones.
| LetterWise offers reduced production overhead |
By installing the same 80 languages into every phone, a manufacturer
can avoid costs in software configuration management. All phones can
be shipped to all regions without the need for special builds to
install language databases. All phones use the same amount of memory
for language databases, so there is no complex juggling of
applications depending on language memory. Phones do not need to be
linguistically pre-configured for a particular region, a practice
which creates inefficiencies in inventory and limits flexibility.
| What other advantages does LetterWise offer? |
There is only one predictive text entry method that makes it possible
for a manufacturer to take advantage of the linguistic market
opportunity described above: Eatoni's LetterWise.
There are a number of other important ways in which LetterWise
distinguishes itself from dictionary-based methods such as T9 and
eZiText. These include the ability to enter non-words, simpler user
interface, and offering consistent text entry in all areas of phone
functionality.
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