Reddit is a growing source of leads and insights for seemingly any business. Reddit posts rank organically for many Google queries and appear frequently in the “Discussions and forums” search result section.

The posts — all user-generated — reveal brand awareness, sentiment, and much more.

Here are four AI tools to search, analyze, and summarize content on Reddit.

1. GummySearch

GummySearch analyzes Reddit to:

• Locate and connect with customers,
• Search with advanced filters,
• Track keywords related to a business,
• Summarize and extract insights from posts.

To start, search Reddit using one or more keywords and select Subreddits to engage with. GummySearch will then create a dashboard and assign categories to the active discussions, enabling further discovery.

Filtering by keyword also provides a quick summary of every thread and a link.

GummySearch helps monitor Subreddits and engage with discussions relevant to your company or product. It’s handy for learning customers’ pain points, brainstorming content ideas, and generating sales leads.

The free plan is limited to 50 searches. Paid plans start at $29 a month and include keyword alerts, content insights, Subreddit analysis, and more.

2. Marketing Blocks

Marketing Blocks is an AI-powered content-generation suite that integrates with Reddit. Input a keyword, and the tool will pull related discussion titles from Reddit and add them to an on-platform content brief. It then generates an AI response to those titles.

Marketing Blocks is helpful for addressing prospects’ concerns and suggestions, unavailable via traditional keyword research.

Paid plans start at $47 per month with a free five-day trial (credit card required).

3. GigaBrain

GigaBrain searches Reddit by keyword and summarizes the findings using generative AI. Clicking on any listed Subreddit enables additional filtering. Further down is the list of threads and comments based on the query, to analyze and condense.

GigaBrain reveals discussions on Reddit for a brand, products, and competitors. It’s also helpful for discovering the words and phrases of consumers to include in your own content.

GigaBrain is a cloud-based platform with a companion Chrome extension. Both are free.

4. Profiler

Profiler is a free AI-powered Chrome extension to analyze the activity of any Reddit user, streamlining outreach and audience research.

I ran the tool on a user profile. Here are the results:

• Interests: The user is interested in podcasts (specifically “LightsCameraPodcast”), movie and television discussions, sports commentary (e.g., “PardonMyTake,” “barstoolsports”), and seems to have a particular focus on “KingOfTheHill,” “LOTR_on_Prime,” and local Connecticut topics.

• Profession: Indicated being a former teacher in 2018; current profession unknown.

• Sentiment analysis: Overall mixed sentiment, with many negative comments (“hate,” “stupid,” “worry,” “bad”) balanced with some positive expressions (“thanks,” “great,” “love,” “awesome”). This user expresses strong opinions with a sense of humor.

• Political leanings: No explicit political stance observed, but does not shy from harsh criticism, which may imply skepticism toward various subjects.

• Psychological traits: Critical, candid, possibly dealing with a past of loneliness or dissatisfaction (e.g., from the heartfelt post about the podcast). Uses humor as a coping mechanism. Opinionated.

• Gender: Likely a male given the use of “brother” and other context clues within the comments.

• Religion: No direct information provided.

• Origin/ethnicity: Likely American, specifically from or has lived in Connecticut, as evidenced by repeated references.

• Behavior patterns: Engages frequently with entertainment-related content, is critical of media content, and often interacts in community discussions with humor and sarcasm.

• Bot or human: Human user based on the diversity and personal nature of posts and comments.

• Other: Engages predominantly in communities associated with popular culture and entertainment. Seems to appreciate humor but also has moments of serious reflection. Formerly engaged in a long-distance relationship and faced personal struggles, which he overcame with support from his podcast community.

The new generation has quickly become obsessed with payments personalisation. While personalisation has firmly established itself as a mainstream feature in Europe and the US, it still has considerable room for growth in emerging markets. One startup tackling this issue is Lune.

Research from Amazon Payment Services has shed light on the evolving preferences of younger generations and revealed that Gen Z in the Middle East and Africa (MEA) region generally prioritise personalisation over privacy. As a result, organisations must do all they can to ensure personalisation demands are met.

However, regional challenges are stopping organisations from capitalising on international technology. Tackling the problem at its core, Lune is a plug-and-play solution that enables companies to build personalised customer experiences while gaining insights from their customer spending patterns.

It converts raw customer payment and transaction data into data points using proprietary AI technology. Lune serves clients in the UAE, KSA, Oman, Bahrain, and Qatar. The company takes a localised approach to the quality of the data and a simpler integration journey based on rest APIs in comparison to the lengthy and complex journey required by their competitors.

To get a greater understanding about the importance of personalisation and how Lune can help, we sat down with the company’s co-CEO and co-founder, Helal Tariq Lootah.

How does Lune stay ahead in technology and user experience, and what are the future plans for doing so?

We have a variety of great use cases stories, but one of my favourites comes from our first bank client.  It is no secret that personalisation is vital for organisations in the modern era and as such knowing your clients’ needs is of the utmost importance. Our first client was struggling with this as they were having trouble understanding where customers were spending their money.

As a result, our client wanted to make a new financial product – namely a credit card. They knew what segment of their customers they wanted to design it for but they couldn’t decide on how to design it. Organising surveys and reviewing results, then hiring consultant management firms to help them decide – it was all a costly process. Not only that, it would take time too – probably around six months.

I suggested the option of letting us run our analytics engine within the bank. After all the data of the segment they wanted to tailor their product for was there – just buried deep. This sort of data is not easy to access when legacy bank infrastructure is being used. We went ahead with running our engine for the bank and after just a couple of months, we were able to show consumers’ favourite brands, where they were spending their money, what categories they liked the most and what they really cared about.

The data was always there – we just made it digestible and actionable. Furthermore, we were able to identify that many consumers were not making the most of the wealth and investment services the bank was offering – creating the awareness and opportunity for our client to act on the information.

What challenges did Lune face in its early stages and how were they overcome to establish a successful fintech business?

The Middle East is ripe with challenges, especially for startups – over the last few years there have been a lot of new business models. In fact, when we started, we weren’t a B2B business, but rather a B2C. We wanted to help individuals understand where their money was going. However, that was when we discovered the deeper technical problem, which was that the quality of financial and payment data is extremely messy. Simply put, it was unstructured and could not be used by an upcoming fintech or bank.

Once we realised that, and pivoted to becoming a B2B, the main challenge we had was establishing an identity. It took a lot of effort to become a reliable, unique, innovative solutions provider in the early days.

Another challenge has been understanding market dynamics. Unlike Europe, where you have one, integrated market, or the US which is one massive market, here, we have a lot of segments and each one is completely different. For example, the market in Saudi Arabia differs massively to one in Egypt. Learning how to do business in each specific segment was a challenge, but one we have overcome!

How did AI help you pivot from a B2C to a B2B?

Originally, we had a simple B2C personal finance management app. It relied on open banking rails and, given the ongoing development of that tech in the region, that in and of itself was a challenge. But the main issue arose when we got the data – it was obscenely bad. We couldn’t get our features to work because the quality of data was just unusable.

It didn’t identify transactions properly. For example, if you went to a burger shop, it wouldn’t tell you that you spent money at the shop. Instead, it would tell you the family name of the owner. As a customer this doesn’t help much and limits the value of the data.

Consequently, we started to search for someone that was tackling this issue, but the more we looked, we couldn’t find anyone that had a working solution here in the region. International players simply said their products wouldn’t work in our region. So, we took matters into our own hands and decided to tackle the problem.

The service was originally built using basic rule-based engines, but that quickly reached its limit and we had to expand in order to add new features in line with our ambition. That’s when we adopted machine learning and its different forms.

How is Lune staying ahead of the curve in terms of technology and user experiences? And how is it going to continue to do so in the future?

In our field that you need to constantly innovate, adapt and listen to your clients. Specifically, when it comes to the hard questions: ones that need daily work. One great is example is tackling localisation issues. One of the biggest challenges we had in Saudi Arabia was that we needed to start working with the Arabic language. We overcame this issue, but were then faced with another. There are Arabic words with English letters.

Therefore, we had to establish a way for our engine to understand these small nuances and make sense of them. This sort of research and development is constant and that’s how we’re keeping ourselves at the forefront.

Secondly, it’s really about understanding the needs of the clients here in the region. Financial institutions can no longer rely on services from other parts of the world. Sometimes, services that are not designed for this region won’t necessarily work. Regulations are complicated and knowing how to tackle each countries individual requirements is very important. Now, firms are valuing this more than just core technology offerings. Ensuring we are a partner that can offer more than just tech is another way we’re staying ahead.

How does Lune use customer transaction data to improve the financial experience and provide unique insights to users?

We are helping the vast majority of users understand their finances. Ninety per cent of the region’s customers don’t understand the specifics of their data and this is primarily for two reasons. The first, is the quality of data. It’s a global issue but especially in the region, you can’t classify transaction spending easily.

The current state of merchant categorisations codes is often inaccurate leading to confused customers when they go to check their accounts. Financial institutions realise they must invest to ensure clarity for their consumers.

Using our services, firms unlock the ability to access a goldmine of actionable data which helps them understand consumer spending, which in turn results in a better consumer experience and understanding and opening up new revenue streams.

Are there plans down the road to expand globally and offer this service across the world?

At Lune, our ambitions are to primarily serve the MENA region and other emerging markets because these are the highest potential markets where we’re seeing the. Compared to 2018 or 2019, we’re now seeing a huge boom in the region. Here we will highlight that after we have established ourselves in our main market we will assess whether to expand to Europe and the US.

Final thoughts

The GCC and UAE has always exceeded when it comes to banking and it has a lot of achievements. However, when it comes to digital banking, there’s still a long way to go from the perspective of the end user. Today, there has been progress and firms are definitely upping the ante when it comes to providing better consumer experiences.

I’m very excited for the next three to five years in our fintech ecosystem and I’m very optimistic for the future.

Here we will highlight that after we have established ourselves in our main market we will assess whether to expand to Europe and the US.