A mobile application that helps Instagram users find perfect hashtags for their posts
Mary Boyagi, the founder of Hashtag Hound, came up with the idea for this application after wasting hours trying to find relevant (and popular) hashtags for her Instagram account. Her struggle prompted Mary to create this smart tool that sniffs out the exact hashtags you’re looking for – in seconds!
Our job here at SteelKiwi was to turn Maria’s business idea into a mobile application for iOS and Android and to develop an algorithm for smart hashtag selection. As a result of our fruitful collaboration, Hashtag Hound now helps thousands of Instagram users find the most apt hashtags for their posts and increase their likes and follows by hundreds or even thousands.
From corporate accounts to private accounts, hashtags are one of the best ways to do targeted social media marketing (SMM) on Instagram. With the right SMM strategy, you can make a product, service, or brand go viral, thus increasing both revenue and popularity. For models, photographers, and other artists, the right hashtags may increase their chances of getting their work known and may even lead to fame and success.
With Hashtag Hound, you can rest assured that whatever your goals, the app’s algorithm will generate the best possible hashtags for your needs. Hashtag Hound was specifically designed to make getting to the hashtag top lists a stroll in the park.
When creating the design for Hashtag Hound, we focused on making it as easy as possible for users to generate hashtags.
To achieve a minimalist design, we decided to go with bright yet unobtrusive colors. We made the app’s interface efficient, offering only the most important features and controls so that people don’t get distracted.
We also added a hound character that follows users through the most important parts of the Hashtag Hound experience.
The idea to use a hound in the Hashtag Hound logo was very enticing. However, a hound graphic loses all of its awesome details when shrunk to the size of a mobile app icon. Therefore, for the app’s icon we decided to go with a minimalist “H” turned into the hashtag symbol (#).
We found a turquoise color scheme the most appropriate, as it’s bright and calls for attention, meaning users won’t miss the icon on their screens.
We hand-drew several sketches of the platform’s mascot, the hound. After our client had chosen the one she liked most, our designer turned it into a bright digital illustration. As a result, the hound is now adored by hundreds of Hashtag Hound users and is the company’s official symbol.
API and module for client part. The core of Hashtag Hound, a Python/Django backend server bound to PostgreSQL, offers a REST API that’s connected to both the iOS and Android applications. This REST API is powered by the lightweight RESTFul framework Restless. For all token-wise operations – such as authentication and requests for password resets and changes) – we used Pyjwt.
Data collection module. As the main purpose of Hashtag Hound’s backend server is to collect Instagram hashtags, we used the Instagram_Private_API. All data collection procedures are scheduled and run by Celery. In order to make data collection fast and reliable, we decided to go with the Tor proxy. Currently, our server is set up to run five Tor instances, meaning that up to five web clients can request Instagram data at once.
We wrote the Hashtag Hound app for Android in Java, which has many times proven itself to be a comfortable and stable programming language. Our choice of architecture was simple: the Model-View-Presenter (MVP) Android architecture allowed us to produce clear and neat code, which can help greatly when testing various approaches to business logic. Plus, the fact that this architecture is so easy to read and comprehend means that any developer can quickly understand the app’s structure and make necessary changes without having to disrupt the existing business logic.
For the REST API interaction, we used the stable and popular Rx + Retrofit combination. We used Crashlytics by Fabric IO to monitor bugs and publish new versions of the app among team members. As for font management, we decided to go with the open-source Crashlytics library. We also implemented such libraries as Picasso and H6ah4i/Android-AdvancedRecyclerView to provide a smoother UI experience.
The Hashtag Hound application for iOS is written in Swift, a modern and powerful programming language. For the iOS app, we decided to go with the Model–View–ViewModel (MVVM) architecture and the Service-Oriented Architecture (SOA), as these fulfilled both our requirements and our client’s expectations.
Hashtag Hound is network-based, so we decided to implement Alamofire for REST API interactions, which in turn is powered by ObjectMapper for model management. Kingfisher is used to load and cache images. Every API call is observed by a network activity indicator, while error management is performed by custom extensions and structures.
We used several animation frameworks (Spring, Cheetah) to achieve a high-quality user experience. We focused on tension, velocity, and damping – each and every animation was implemented with its own carefully tailored parameters. Even the simplest of transitions were custom-made to satisfy design requirements. Further, we adjusted some frameworks, extending or modifying them to meet particular needs.
We also implemented support for universal links to share functional and URL schemes. This allows users to open the app through a link from any source (email, text message, Facebook, Slack, Telegram, Notes, etc.). We paid close attention to even the tiniest of details, such as Instagram deep link integrations and login security powered by Keychain. All of this together resulted in a high-quality modern mobile application with beautiful design and seamless animations.
Behind Hashtag Hound is a complex algorithm for smart hashtag selection. This algorithm works in two steps: first, it generates a list of influencers (influential accounts that are helpful for selecting relevant tags) and then it actually generates a list of hashtags. When selecting influencers, Hashtag Hound runs candidates’ accounts through a complex algorithm that determines whether their account activity and statistics match predefined criteria. For a hashtag to be selected, it must be used by a certain number of influencers – this way, Hashtag Hound knows that the tag will be successful in improving your account’s following and conversion rates.
Before generating hashtags, you need to specify a language, a date (like the 4th of July or the 31st of December, etc. - tags tied to certain dates tend to be quite popular), and a place with which you want your hashtags to be associated. In essence, you’re making sure that you get hashtags that are relevant for the US in 2017 and not for Spain in 2003 (unless, of course, that’s what you’re looking for).
By choosing among a number of categories and subcategories, you can decide on the exact topics around which your generated hashtags will be based. Hashtag Hound already has many categories: Travel, Photography, Fashion, Beauty, Fitness, Luxury, Social Change, and so on. This list will continue expanding, giving you more categories to choose from and, as a result, making your experience with this app even better.
Hashtag Hound lets you form favorite lists of your most loved hashtags. This way, you’ll always have your greatest hashtags within one click, which is especially comfortable for those who either have a real passion for Instagram or whose business is based on this platform. You can even exchange favorite lists with other users, allowing you, your friends, and your business partners to stay on top of the Insta game.
They did everything exactly the way we wanted. Although their delivery time was faster than anticipated which caused a few problems, they impressed with their supportive understanding and accurate development of the app. Steelkiwi's strengths of superior organizational skills and excellent problem solving make them a reliable partner.