One of the first examples to demonstrate how Mobenzi can be used in a commercial context will be through the launch of a new vertical solution for researchers called SMS Insight.
Traditionally, when it comes to gathering data via SMS, researchers have two rather ungainly options if they wish to collect anything more than the simplest one word response:
- Require that respondents structure their feedback in some way (e.g. comma delimited) or;
- Solicit answers one SMS at a time, with responses still needing to be confined to a reasonably limited vocabulary.
But what if you could ask a question (or several questions) in an advert, SMS or display and allow respondents to answer in free text – but still be able to analyse the data using quantitative techniques? That’s precisely what SMS Insight offers: the ability to derive structured results from free text responses. Here’s how:
1. Pose the question
Your message can be communicated via SMS, on TV or radio, in print ads or outdoor displays, on product packaging etc.
e.g. An advert asks: “What would you change about our company? SMS your name with your ideas to 35xxx”
2. Solicit feedback in plain text
Respondents simply reply via SMS – in their own words – with no fixed formats, keywords or codes required.
e.g. “I wish your staff would be more friendly. Niki”
3. Use human intelligence to crunch the responses
Our panel of mobile workers use their innate human ability to structure, classify and quantify each response by answering simple questions based on your exact analysis requirements.
e.g. “Is the response about our products, prices or service?”; “What is the respondent’s name and if possible, their gender?”
4. Integrate and act on the results
What was once raw, unusable SMS data is transformed into rich, structured information that can be used to inform business strategy, evaluate performance and identify opportunities.
e.g. “14% Products, 12% Price, 74% Service”
Interested in conducting research using SMS Insight? Please get in touch with us to discuss your requirements.
I came across an interesting article on ZDNet entitled “Inside India’s CAPTCHA solving economy” which discusses how Indian “data processing” companies are being used to solve CAPTCHAs, presumably to circumnavigate security measures put in place by companies to prevent spammers from registering bogus accounts for the purposes of spamming and other unsavoury activities.
Firstly, for those unfamiliar with what a CAPTCHA is and the purpose of it, here’s a definition from the official CAPTCHA site:
A CAPTCHA is a program that protects websites against bots by generating and grading tests that humans can pass but current computer programs cannot. For example, humans can read distorted text as the one shown below, but current computer programs can’t:
By using real people to solve CAPTCHAs – at a very low price – spammers are able to overcome the useful function of the CAPTCHA in an economically viable fashion.
Mobenzi could be used to solve CAPTCHAs as the Mobenzi task would simply need to prompt the agent to review the image (the CAPTCHA) and respond with the actual text (thereby solving the CAPTCHA).
The example of CAPTHA solving opens the broader question: What level of monitoring and/or censorship (if any) should be imposed on those submitting tasks for processing by the Mobenzi platform?
Naturally, when Mobenzi is commercially released we will stipulate terms of use which will outline the sorts of activities which are prohibited. But is this enough? This particular example introduces some interesting issues worthy of consideration. Spamming is obviously prohibited by legislation in most countries and solving a large number of CAPTCHAs using a human labour force is rather likely to be used for this purpose, but is the process of using real people to solve CAPTCHAs automatically illegal?
Following this line of thinking, what other potentially malicious activities could be supported by the Mobenzi service and how should we guard against this? It may be infeasible, and possibly unethical to screen tasks submitted by commercial users.
One possible solution may be to use the CAPTCHA solving ability of the Mobenzi platform to prevent spammers from doing so. A small number of CAPTCHAs from major sites typically attacked by spammers could be processed by us and compared with the images requested to be processed by Mobenzi users. If a statistical match is discovered, the offending user could be sanctioned immediately.
It’s early days yet – but these types of concerns will be important should the Mobenzi service prove successful to ensure that it is used for legitimate purposes only.
We went through hundreds of options when we were thinking of a name for the service. We ended up crowdsourcing votes for peoples’ favourite names over Yammer - the microblogging service we use at Clyral.
isiZulu is the language of the Zulu people with about 10 million speakers, the vast majority (over 95%) of whom live in South Africa. It is the native language in the KwaZulu Natal province where our Clyral offices are based. Since we are focussing our efforts on predominantly Zulu speaking people, we thought it would be very appropriate to adopt part of the language in our name.
In the end, Mobenzi came out on top. We combined the first half of the word ‘Mobile‘ (a little clichéd perhaps) with part of the Zulu word for ‘task or work’ which is ‘umsebenzi‘. The name therefore means ‘Mobile Work’ which we hope will help carry the concept through South Africa’s Bantu (Including other similar African languages) speaking population and will be catchy and easy enough to pronounce for others.
