rasa.io ai powered smart newsletter feature developments

Top 6 Exciting Feature Developments for rasa.io Smart Newsletters

At rasa.io, we are dedicated to helping our clients communicate with their members in a meaningful way with our Smart Newsletters. We are always thinking of ways to grow and improve our platform, so that our users have all of the tools they need to easily craft their communications. Whether those are tools for email design, content curation or valuable insights, it is our goal to provide the best user experience possible. With that said, we are very excited to announce some of our new feature developments!

1. Updated Articles Analytics Page

What’s New:

More open and click data. See the number of unique newsletter opens that included the article as well as the click rate and number of unique clicks for each article and better understand article-by-article conversion rates.

Click rates specifically for AI-recommended articles. This allows you to see our AI at work by showing the percentage of clicks per recommended article.

More valuable insights. Filter your most clicked on articles by month, week, day or a custom date range to gain an understanding of what current events or topics were most interesting to your members.

rasa platform new feature development

2. Share to Social Integration

Share your top articles to social media. Now you can promote the highest trending articles within your industry on your Twitter and/or LinkedIn account with the click of a button.

rasa platform new feature development

3. Revamped Sources Analytics Page

What’s New:

More open and click data. See the total number of articles from the source that were included in unique newsletter opens, the total number of unique clicks on articles from the source, and better understand your source-by-source conversion rates.

AI specific click rates by source. This shows the percentage of clicks on AI-recommended articles for a specific source.

Group data by source OR publisher. You can now filter your source data by the original publisher. For example, if the rasa.io Twitter is one of your sources and tweeted a link to an article from The New York Times, you can now see the data for that specific publisher. Use this page to gain better insights on popular sources or publishers that you may not have originally identified as sources.

rasa platform new feature development

4. AI Knowledge Tier Analytics

Valuable member data and AI insights. Our AI groups your members into 9 tiers (A through I) according to how many pieces of data it has gathered on an individual, the first tier being 0 and the last being 300+. This page will show you the correlation between higher open and click rates for members we know more about.knowledge tiers page G rasa new feature devlopement

5. Today's Newsletter Info

Real time analytics. Track your opens and clicks in real time to see engagement by each hour of the day.

Subject line success. See which AI generated subject lines are performing and converting the most opens and clicks.rasa platform new features development

6. Advanced Post Editing

Adjusting article titles and descriptions. Infuse your own commentary or adjust the copy for any article in the Posts Page.

Upload an image. Use our image upload feature to adjust or add an image to be associated with a certain article.

Ready to Make Your Newsletter Smart?

Request a demo today to learn more about all of the tools rasa.io has to offer around automation, personalization, and content curation.   


ensync corporation rasa.io partners using ai to help associations

enSYNC and rasa.io: Leveraging AI to Personalize and Automate Newsletters

We are proud to announce our recent partnership with enSYNC Corporation!

enSYNC and rasa.io are partnered with the goal of furthering our missions to help associations use helpful and innovative technologies to propel their missions forward.

About enSYNC

enSYNC’s mission is to help their clients make distinctive, lasting, and substantial improvements in their performance and to make a measurable difference in the success of their association or nonprofit organization through increased membership, donor support, or engagement.

One of the ways in which enSYNC helps associations achieve success is by offering a variety of different software solutions. rasa.io is proud to be one of enSYNC’s preferred technological platforms.

Ready To Dip Your Toe Into AI?

In a recent blog post, enSYNC outlines the emergence of artificial intelligence in the association world and how to begin utilizing it in a way that aligns with your overall purpose. The article goes on reference the benefits of rasa.io AI technology and our ability to automate and personalize your email newsletter. This personally customized content branded by your organization yields higher engagement rates and creates a platform for increased monetization.

Join forces with rasa.io and enSYNC to propel your association’s mission forward

Check out the rasa.io product page on the enSYNC website! And get in touch with us today if you are interested in using AI to better inform your members and to automate the newsletter creation and distribution process.


computers showing association members engaged using scalable artificial intelligence

Building Scalable Artificial Intelligence Systems That Keep Your Association’s Members Engaged

Artificial Intelligence software systems demand innovative development and deployment approaches.  The techniques that have been honed over the years by companies and software engineers do not scale effectively in the presence of AI systems. We understand these challenges, so we have built our AI solutions using methods that give us the ability to improve our systems quickly and deliver better content for your association’s membership.

Where we have come from

Traditional software systems have been built following a standardized set of practices that have evolved from collective experiences, gained by thousands of large and small companies, over many years. Software developers will quibble about the differences between Waterfall and Agile, Scrum and Kanban, but these different techniques and approaches represent variants on the same general approach: a degree of planning, followed by development to meet some specs, then testing to validate the adherence to the specs, and finally deployment and monitoring of A, B, C and D.

Do you measure turnaround time in hours and points with an Agile development cycle? Do you measure time in months with detailed FDD specs? The difference is in the scope of the steps (and in perceived chances of success with the difference in scope!), but the general approach remains the same.

For years, the primary push in this cycle has been to shorten feedback loops: get features to field as fast as possible in order to get feedback fast. Early feedback - bringing an idea from whiteboard to field - enhances the likelihood of success in the form of customer satisfaction. Unit and Integration Tests, Continuous Integration, Story Boards - many techniques have evolved to help development teams move faster with increased confidence in the features they deploy.

Where we are going

Artificial Intelligence and Machine Learning systems introduce new and different challenges in the software development and deployment cycle, challenges that demand innovative solutions.

First and foremost: Artificial Intelligence systems crave data; they need data from which to learn. One programmer’s adage says, “There are only 3 numbers: 0, 1 and 2. Everything else is just a generalization of 2.”  Many systems could be tested following that adage: enumerate a small number of conditions, then test those conditions and the corresponding edge cases. AI systems throw that adage out the window. These systems do not work without mountains of data to evaluate. The need for data introduces 3 specific challenges:

  1. Data Acquisition: We must first build tools to gather enough data to be able to evaluate an AI system. Until we have that data, we are limited in our ability to build systems to consume it.
  2. Development Time: Consuming data and evaluating it via AI systems can be computationally expensive. Development cycles that used to measure in seconds from deployment through testing may now be measured in hours: modify the AI system, deploy it, then run through the learning cycles.
  3. Result Evaluation: AI systems generate tons of predications given the massive amount of data pushed in. Those outcomes are based on the machine learning, which is itself based on the data consumed. In other words, there are too many outcomes to enable testing all of them individually. And the outcomes are not known apriori in a way that a Unit Test could be written to evaluate the model output.

rasa.io is paving a new path for associations to use Artificial Intelligence

The techniques software engineers have used in the past cannot scale to support the development of machine learning systems. At rasa.io, we have adapted our processes and tools to enable us to develop and deploy enhancements to our AI engine more rapidly. Our serverless platform, built using Amazon’s Lambda, EMR and RDS services, allows us to horizontally scale our platform, reducing the time required for our AI solutions to build their predictions.

Reducing the turnaround time for processing the vast amounts of available data gives us the flexibility to develop improvements to our AI engine faster. What this ultimately results in, is a sophisticated machine that informs you on what your association is interested in and thus how you can best communicate, on a daily basis, with your members.

We recognize that the growth of our AI is critical to the delivery of the best content for the members of your association.  We are committed to staying ahead of industry trends and technologies to ensure that our AI engine remains at the forefront of personalized recommendations. This allows us to get more relevant content delivered to your members and understand what motivates them. Learn more about how rasa.io can engage your members today.


Association member uses artificially intelligent smartwatch

No Longer Intangible AI: Ways in Which Machine Learning Impacts Your Daily Life

Artificial Intelligence is working for you on a daily basis, in ways you might not even realize. Computer scientists have been developing machine learning technology for decades, but we are finally at a turning point with the development of AI: recent breakthroughs with regard to machines understanding human language, behavior, vision, and speech intonation have leveraged artificial intelligence to the next level and woven it into the fabric of our daily lives.

Artificial Intelligence is at your service

Sophisticated advances in machine learning around the most complex patterns of human behavior support AI assistant tools in meeting your needs. Siri, Alexa, Cortana, and Google are not programmed to respond to your requests by delivering one specific output based upon one specific input, rather, these virtual assistants evolve their responses to your inputs over time, as they learn more about your wants, your behaviors, and the aggregate complexities of human communication. The more you draw upon these services, the more they learn about how to serve.

Machine learning helps deliver engaging information

You might spend several hours every week ridding your inbox of emails containing irrelevant information. Sophisticated developments in artificial intelligence help reduce the time it takes to organize your inbox and ensure only the most relevant information gets to you. Google employs tools to smart-categorize your inbox and send completely meaningless content to your junk folder. Taking it even further, when it comes to the specific content in your emails, Artificial Intelligence can be used to populate the content within your messages, to ensure that you are only receiving information that is specifically curated for your consumption

AI informs your commute

The data that Google maps and other navigational tools synthesize to inform your commute is a form of machine learning. These tools pull in anonymized data from smartphones in any given area - regarding traffic flow and speed, construction sites, and traffic accidents - and then direct you along the most efficient path toward your destination.

Intelligent programs deliver information about your customers or members

We have evolved past the point in which only mammoth retailers like Amazon can harness the power of AI to understand those whom they serve. Instead, the technology is attainable and can help many different kinds of organizations learn about their members, customers, or constituents, in order to engage them and drive revenue. As organizations learn about how their people want to shop, read, or learn, they can specifically tailor their content to match those individual needs.

AI is already at work for you

Although the prospect of machine learning affecting our day to day might seem daunting and intangible, in fact, it is more than likely already at work for you. Don’t think of the technology as something scary or intimidating; instead, think about how it is already doing its job, making you more productive, helping you run your organization more effectively, and smoothing your daily interactions.


Association member checks individualized email created using artificial intelligence

3 Ways to Experiment with AI at Your Association Right Now - Part II: Artificial Intelligence for Curating Individualized Email Content

Artificial Intelligence does what isn’t humanly possible given an association’s resources. It can find non-obvious correlations and patterns in member and customer data. It can interpret vast quantities of content and make sense of it.

The media loves speculating about AI’s potential but there’s no need to get caught up in the hype. The best place for your focus is AI’s practical applications for your association right now.

Organize and curate information automatically

It’s nearly impossible to keep taxonomies current and accurate because staff must struggle to constantly review and tag content. With AI, you never have to work on a taxonomy project again.

Natural Language Processing (NLP) is an AI application used to understand the meaning of written or spoken language. NLP makes automated taxonomies possible. It works in the background doing the heavy lifting for staff so your taxonomy is always up to date.

But most of what your members read is from external sources; what about those? AI can analyze and tag external content too. You can now provide a service your members have only dreamed of: you curate the industry information streaming by them each day.

Deliver daily, individualized, industry-related news to your members

Now your members don’t have to spend time skimming through junk trying to find treasure. Instead you send them a daily news brief containing personalized recommendations of content from internal and external sources that are most relevant to them based on an analysis of their data. That value is worth the price of dues and then some.

We’ve learned in our projects with associations that AI-curated content drives higher engagement, i.e., more email opens and clicks. As time goes on, AI analyzes a member’s behavior and learns what they’re interested in as well as their format and reading time preferences. This behavioral data is more reliable than self-reported data—as they say, actions speak louder, and more truthfully, than words. Associations are using what they learn about their members’ interests to make decisions about future conferences, educational programs, and association marketing content.

As the software collects and analyzes data, and algorithms adjust, engagement metrics continue to increase. A project of this scale is not humanly possible without the assistance of AI.

Learn more about engaging your members with artificial intelligence

Rasa.io engages community members by curating content and delivering daily, individualized newsbriefs. If you are interested in engaging your membership by catering to their unique interests, learn about how rasa.io can help.

This blog is the second part of a 3-blog series designed to teach associations about how artificial intelligence tools are accessible and effective for decreasing the association engagement gap. Read Part I: Using Artificial Intelligence for Website User Engagement.