Introduction

DaniWeb Connect is a network of community-based apps that pool their resources by sharing data about users they have in common. By building your app on the DaniWeb Connect platform, you can gain a much broader perspective of your audience. The amount of data that you have access to about each of your users continuously grows in real-time as the network evolves.

The DaniWeb Connect API consists of a user matching and chat API. Our patented algorithm uses machine learning to match users based on the data we learn about them, and their behavior, as they interact across the entire network. The result is the ability to match people on the likelihood they are to mutually benefit from the connection.

Single Sign-On

DaniWeb Connect uses the OAuth protocol to operate as a single sign-on platform. When your users log into your app with our secure SSO, you immediately gain access to their profile, connections, behaviors, and data points from across all Daniapps that they choose to participate in. If you'd like, your Daniapp can give your users the ability to communicate across communities and platforms.

In the example diagram depicted below, we have two users who have logged into an application for the first time: Dani and Fred. We immediately know three things about each of them.

Dani logs in …
Tech entrepreneur
Currently hiring
Member of a hiking group
Fred logs in …
Freelance front-end developer
Tends to talk to people interested in outdoor activities
Tends to engage heavily with tech founders

We see above that, while Dani is a tech entrepreneur, Fred tends to heavily engage with tech founders. While Dani is currently hiring, Fred is a freelance developer, perhaps looking for work. And, while Dani is a member of a hiking group, DaniWeb Connect knows from Fred's behavior across other Daniapps that he tends to talk to people interested in outdoor activities. It seems like Dani and Fred should meet. We will continue discussing Dani and Fred later in this document.

Audience Segments

Our network is comprised of multiple audience segments. Audience segments represent a standalone collection of users. An example of an audience segment might be members of a single community or group.

Each Daniapp is associated with one or more audience segments. Daniapps are self-contained in that they only have access to members of the audience segments in which they are associated.

Audience segments get populated by attaching Daniapps to them. Audience segments can be configured to automatically join users who log into specific apps. You can also manually join users of your app to any audience segments you own. If you built an audience segment, you may share it with other application builders for them to associate with their own Daniapps. Therefore, Daniapps can exist that simply leverage audience segments built by others.

As an example, Developer A built a blogging app, in which its users are members of Developer A's audience segment comprised of digital publishers. Developer B built an advertising solution, utilizing his own audience segment consisting of digital advertisers. Developer C may then build a marketplace app, attached to both audience segments, that connects digital publishers with advertisers. In this case, Developer C was able to create a marketplace app which was instantaneously seeded with users benefiting from connecting. The marketplace app is able to use our user recommendation engine to expertly match publishers with advertisers by considering their user behavior within the first two apps. Meanwhile, users of the first two apps gain additional functionality, relevant to them, with their existing login credentials.

Make Money

It is entirely free for users of your app to interact and engage with each other. DaniWeb Connect charges a small micropayment for your users to introduce themselves to new connections in the DaniWeb Connect network whom are not also users of your app.

In the example prepared above, users of the first two apps would be able to interact with each other for free. However, a blogger using Developer C's marketplace app would have to pay to reach out to an advertiser not already also using the app. The fee is algorithmically determined based on the likelihood that, upon being introduced, they will engage in a mutually productive, goal-driven discussion that satisfies both of their interests. In many ways, this acts as a barrier against users being solicited by those irrelevant to them, or by those attempting to cast a very wide net.

The payment may come either from the end-user or from the app itself. You may choose to have your application pass the individual fee onto your end-user, charge a premium, function as a flat-fee SaaS, absorb the costs, etc.

User Matching

The foundation of our matching algorithm is that, regardless of the Daniapp being used or the reason for connecting, the single common denominator is the desire for instant gratification. Whether it's for personal dating or to seek a new business opportunity, being fed the most targeted people is less than half the battle. In fact, the "right" people are the wrong people if they don't respond in a timely manner. Much more importantly is the likelihood that users will engage in a productive conversation shortly after an introduction, satisfying the needs and interests of both parties. To that end, our algorithm uses machine learning to focus on user behaviors across all the Daniapps users choose to participate in, and discover commonalities and patterns between whom they choose to respond to most often. It then uses this data to predict the best potential mutual matches. Each Daniapp in the platform can then additionally train the algorithm to perform a weighted search and filter on all potential users based on data known about each user from across all Daniapps in the network.

Gain Insights

An infinite amount of data points may be attached to each individual user. The data is acquired initially from profiles that the user fills out, third-parties such as their social network profiles, geolocation information, and various behaviors and interactions that are monitored. From there, each Daniapp may choose to set additional data points, known as metadata, that it knows about the user. Metadata attached to a user can be anything from a list of their interests to their reputation score within the Daniapp.

The same way that metadata may be attached to individual users, metadata may be attached to individual messages within conversations and group chats. By attaching metadata to individual messages, your Daniapp can incorporate rich messages which include image attachments, Youtube videos, and any other arbitrary data you'd like to associate with individual messages for your own purposes. A CRM Daniapp, for example, may choose to use metadata so that users may flag individual messages for follow-up. Every piece of metadata, for both users and messages, is attached to a privacy setting.

All of the information attached to a user follows them around across each Daniapp that they choose to participate in. In this way, you can learn more about your audience by acquiring data that other communities know about them. Building your app on top of the DaniWeb Connect platform lets you benefit from a well-rounded profile for all of your users, comprised of more data than any single app can acquire. For example, a single user may participate in a real estate Daniapp, which knows their annual household income, a technology Daniapp, which knows their technical skills and expertise, and a career Daniapp, which has access to their complete CV. Each Daniapp is now able to build a more complete picture about their user by gaining insights to other aspects of the person they otherwise wouldn't have had access to. The amount of data that you have access to about your users continuously grows as the entire DaniWeb Connect universe evolves.

Searching and Connecting

The diagram below brings us back to Dani and Fred, who have both recently logged into a Daniapp for the first time. Here, we see that Dani uses the app to perform a simple keyword search, looking for users familiar with Javascript and in the San Francisco Bay Area.

The API's algorithm begins by filtering for users that meet the criteria requested. However, it then goes beyond filters to focus on behavior. As a result, it is able to determine that John and Joe are not good matches, while Fred is a good match for Dani.

Dani performs a simple keyword search …

Javascript SF Bay Area
Search goes beyond filters to focus on behavior
  • John
    Javascript SF Bay Area Doesn't log in often
  • Fred
    Javascript SF Bay Area Hiking in common Responds quickly to job requests
  • Joe
    Javascript SF Bay Area Never replies to entrepreneurs

The benefit is clear:

  • Profile Picture

    Hi Fred, I am looking to hire a front-end web developer for a hiking app that maps local trails.

  • Profile Picture

    Nice to meet you! I'm currently looking for Javascript work. This sounds like a great fit because I hike every weekend and have been looking for this kind of app myself!