Twilert is a new service which aims to bring the ease of Google alerts to the Twitter world. It’s up against Tweetbeep, which has offered alerts for a while, and both offer filtering by location. Twilert does have the edge on flexibility around the selected keywords, specifying both the username of the sender or the recipient of Tweets, and even offering some basic postive/negative attitude reporting.
So it seemed a good idea to find out more about Twilert, and especially how it might differentiate itself further in the future, by speaking to Dan Leach, who is behind the service.
What was the main inspiration for Twilert? Was it something you personally needed for monitoring Twitter in your day job?
The inspiration came about a month ago when I was looking through the Google Alerts I have setup for my various clients (I work in PR and marketing). A lot of the information was dated and I wanted to find a way of seeing what people were really saying and thinking about the brands and products I represent. As an obsessed Twitter fan I wanted to find a way of tracking conversation and opinion on the site without having to sit in front of a Twitter Search page all day. And so, Twilert was born.
There are limited options available to people if they want to monitor “tweets”. Aside from the aesthetic differences between Twilerts and its competitors, the two main advantages include:
- Full customisation of alerts: Twilerts options reflect exactly that of Twitter’s Search service which mean alerts can be tailored by keywords, author, recipient, location, link-location, and attitude (positive, negative, neutral). This means you can filter out irrelevant tweets from your alerts.
- Ease of use: Twilert doesn’t require you to have a Twitter account, nor does it require any technical knowledge of Twitter or search. True story: to ensure the site was as user-friendly as possible, the test subject I used throughout development was my Mum. If she can use it then anyone can!
You’ve obviously built in some quite specific ways to filter messages: by location proximity, whether they include links, and by positive or negative attitude. How are you calculating the attitude of Tweets?
The attitudes of tweets is calculated by Twitter’s emotion algorithm (created first by Summize) which uses certain phrases and words that suggest a positive, negative or neutral phrase and maps them against keywords in the tweet.
It is by no means 100% accurate and will continue to evolve, however it will provide a decent enough snapshot of whether people are speaking positively or negatively about whatever you are tracking.
We have included everything that Twitters allows through its API. With the limited information that is provided with each tweet (author, recipient, location, content) it is difficult to filter them anymore than is already possible on Twilert.
Monetising the service is a long way in the future – Twilert is less than a week old so our focus is 100% on providing a high quality service to our users. However, we will be exploring extended functionality that could be implemented for enterprise users. It is worth stressing though that the basic alert service will always remain free to users.
Twilert is definitely the weapon of choice for anyone looking for regular automated emails which compile your reports within potentially pretty specific criteria. It’s also one of the better looking 3rd party applications for Twitter, and being designed by someone working in PR and Media, it should be well placed to capitalise on the influx of brands and agencies looking to
