2025 Outlook: the top 10 analytics trends SaaS PMs need to know

welcome everyone welcome to the Qrvey webinar today we're going to be talking about a 2025 Outlook at the top 10 know today's agenda we'll do a quick intro to multi-tenant analytics and Qrvey um and before we get into all of the trends that we're going to cover today we'll quickly talk about some of the unique challenges that are facing SAS companies and today we have David Abramson uh Chief technology officer at Qrvey uh leading the presentation uh he is the uh CTO he's got over 20 years experience in analytics and at Qrvey his

role he drives the company technology Direction he's focused on helping software providers expand their products create value from all their data with embedded analytics Automation and self-service data collection so I will pass it off to David take it away all right perfect thanks and thanks everybody for joining us uh on today's webinar I'm gonna kick things off just by doing a brief introduction into you know who Qrvey is and and then we'll dive into the meat of the rest of the presentation but at a high level you know we really are a purpose-built analytics solution for software products and software teams and what that means is we're helping software companies SAS companies deliver

highly scalable and highly secure multi-tenant analytics for their customers as part of their software offerings and so that's really why we exist what we're doing and the problems that we solve and the reason why that's so valuable is the cost savings and the faster time to Market um we work with a lot of SaaS companies who need to deliver Rich analytic capabilities quickly and they want to do that at obviously the lowest cost to them possible and with Solutions like Qrvey we can help achieve those goals by delivering a rich set of analytical capabilities without all the time and without the huge expense and this is actually a pretty good contrast of what it looks like to deliver uh an analytics layer through

Qrvey where we provide all of the tools the apis the embeddable widgets the data Lake the semantic layer all of the custom connectors and Transformations whereas if you had to build this yourself obviously there's a lot of moving Parts there's a lot of other tools and um you know different tools that you're going to have to leverage to be able to deliver that capability which can not only add to the overall expense but also add to the time and maintenance effort it takes to deliver a successful and robust and scalable analytic solution as part of your software offering to your external customer customers and why is that important there's there's obviously a lot of challenges that SAS companies face when it comes to delivering successful analytics and and not the least of which

just the overall complexity of how to organize and manage all the data but there there are different challenges than if you were to say build an analytic solution just for your internal or Enterprise needs right SAS companies trying to achieve successful external facing Analytics you know have to look at it from a different lens than if you were building it for your internal business needs it it has to scale differently obviously you're now dealing with more customers more users larger data volumes the security is different because you're not thinking about it from kind of your own single tenant your own company's business case but more granular multi-tenant control user control has to be there for your end customers has to be wrapped into the

data and and all of those tenant user specific requirements for security purposes and then the overall complexity of data things like how do you mix and blend multiple different Source types maybe customers are bringing some of their own data or how do you augment that with Transformations through things like Ai and machine learning and so there are a lot of different challenges and different pains and it's not just that sort of internal cost center that uh an Enterprise Analytics tool um you know is realized as it's it's not single tenant it's multi-tenant and the opportunities it presents offer you the ability to even create a revenue Center for your analytics outcomes for your end customers so managed by your product teams it's for your external customers

and your end users and it allows you to even Define you know new Revenue opportunities to bring uh successful outcomes for your analytics experience and of course you know a lot of you hopefully understand why you would want to invest in an analytics outcome for your products uh just mentioned the revenue streams opportunity um to be able to build new maybe premium feature sets or add-ons or even deliver custom Professional Services around analytics outcomes but also things like how do you differentiate against your competitors um how do you deliver this capability faster and maintain all of those security and scalability and all the

other challenges around data that we just sort of talked about uh and so there's a lot of great reasons why you would want to spend the time and energy to invest and even monetize the analytics capabilities inside of your product not the least of which is that differentiation angle and we're going to talk about actually quite a lot of these differentiation points when we talk about the the key trends because these really align with a lot of the trends in the industry whether it's delivering more self-service capabilities to your customers doing more with tools like automation logic and capabilities modernizing applications or even bringing data in different ways through data as a service or data collection

mechanisms so all of these are ways not only that you can differentiate your product but also um a lot of the trends that we're going to be talking about when it comes to what's what's happening within the analytics space moving into um this year and Beyond um last point I'll make is this is an initiative where it doesn't have to take a lot of time um and that's again one of the key values that companies like Qrvey bring the ability to get to Market very quickly as part of again product enhancements product enrichments are part of your overall product roadmap strategy you know it can be as quick as a couple of weeks to build that um proof of concept um that allows you to get in front of customers and showcase you know

what are some of the opportunities and potential uh and then even maybe just a few more weeks to launch that initial MVP and roll out these uh Rich analytical outputs to your and customers as part of your production launch within your applications and then all of the opportunities to expand you know come with that so when you think about how you're going to plan and how you're going to make this work in your your product road maps and timelines um this shouldn't be kind of a daunting task in terms of the overall timeline picture as long as you're working with the right tools and the right capabilities to move forward all right so now that we have the uh the introduction out of the way let's talk about where we see the the

analytics Trends uh moving into next year and into the future for SAS products and SAS teams uh and so we're going to focus on 10 key trends that we think are really important to the overall analytic space so the first Trend we're going to talk about is uh AI obviously AI is a pretty hot topic across the board uh but particularly gen a and and what we know is that AI adoption is growing very very rapidly um studies are showing that the usage uh between uh 2023 and 2024 is basically doubled so more and more people are using gen and um what they're using it for is actually quite interesting

because um majority of folks are using it to not only create content but also to do uh data and analytics and analyses so um customers or users or just consumers in general are are more and more used to working with gen AI tools um not only to create their content but to analyze their data so as a SAS business you really have to think about how that's going to impact you how are you going to um include gen AI related features as part of your product um and how are you going to make it easy for your customers to um integrate or work with these types of tools as part of your overall application experience that you're going to deliver to them inside

of your uh software applications uh so what we recommend is thinking about how you're going to incorporate your gen analytics features into your product road map and with uh what we're seeing as far as kind of the main areas of Leverage for Gen it can help in in kind of three main areas one um you can think about how it's going to impact your developers um so gen tools to help them create content um as kind of an overall productivity booster I'm sure a lot of your engineering and Dev teams are already using tools to help them write code well same is true for analytics uh and with you know tools like Qrvey we can help provide enhanced and enrich capabilities to provide that productivity for the development teams

um for power users maybe some of those more advanced and end customers uh along the lines of you know how they want to do data exploration or derive AI powered insights providing uh integrated tools and widgets to allow them to discover new insights through gen AI uh and then even for more basic end users uh giving them chat-like interfaces uh AI powered interface suggestions and recommendations as part of those interfaces that are all powered through gen integration so all of that can be included as part of the overall sort of analytics experience inside of your software product so we we see that as kind of obviously a very very um heavily discussed Trend but something that in an analytic space you

can you can really start taking advantage of today as part of your your your products Trend number two uh is really focused on the automation use case um automation can really drive a lot of what's happening in the analytics capabilities of your product and it can really be part of a very successful analytical implementation and what we've seen is the trend moving towards more and more Automation in general it's it's becoming a very mature set of functionalities across pretty much every organization uh and you know if you're building applications that focus on any of these areas like Finance accounting it or operations um they're already heavily using automation within their

organization so having that as part of your application um would obviously be a very important critical set of features that you could offer to your customers uh alongside whatever analytical outputs and capabilities you're delivering to them inside of the SAS product so obviously what we're recommending here is that automation use cases should absolutely be part of of any customer facing analytic strategy that you're going to develop and these can be add-on tools these can be um additional packages again opportunities for new revenue streams but some of the use cases I think that um we've seen some great success with among our customers is not just things like scheduling of reports or emailing of content but also

being able to allow for things like data driven alerts and notifications maybe even some automation that drives data right s or updates into the source Data Systems uh and then even Integrations so external Integrations maybe automations that drive actions in thirdparty tools or external systems and services and so all of that can lead to a very successful overall automation strategy that's part of your uh analytical outcome in your SAS products for your customers let's talk about Trend three uh which is really about different types of data so how do you connect all of that disconnected data uh semi-structured unstructured data and obviously the trend here is unstructured

data is really just blowing up um you know reports are showing it accounts for nearly 90% of all of the generated data that's out there and um probably don't have to tell folks on the webinar today that the amount of data is just growing exponentially um you know predicted to be nearly 400 zettabytes of data by 2028 so there's going to be more and more data that we have to contend with and most of that data is going to be either semi-structured or unstructured data that uh if you don't have a good strategy for figuring out how to work with that um obviously there's going to be a lot of uh Missing data from the possibilities within your

analytics in your your um your applications so with that um one of the things that we really recommend is figuring out the right way to support multiple data source types um across different structures and models so how do you blend together that semi or unstructured data into your uh SAS product analytics for your customers uh look for tools that allow you to blend that data with joins and unions custom Transformations can help you handle those more complex data types so the semi structured objects and arrays and hierarchical structures of the data um leveraging tools like the AI and machine learning to transform unstructured data whether that's text analytics sentiment

analysis keyword analysis you know all these different options for taking uh unstructured data and making it easily analyzable inside of your application systems is going to be incredibly important for taking advantage of all of this data and then there's lots of other opt opportunities so how do you handle you know custom data pivoting how do you handle in in a lot of SAS companies you know custom generated Fields automatically and again tools like Qrvey can help solve for those types of problems and challenges so bringing together all of that disconnected data to make it usable for your end customers Trend number four you know we're going to talk about self-service as I mentioned earlier you know one of

the key differentiated use cases is the ability to provide more of a robust full self-service experience for all of the users of your application and as you can see you know most users in fact 88% of pretty much all customers expect that there is some form of self-service within any application that they're working with uh and most customers in fact want the ability to independently solve their own problems so the more you can do to provide Rich set of self-service capabilities particularly around the analyses and the data that they're going to work with uh obviously goes a long way in satisfying the demands and needs of most end users in these application

scenarios a complete self-service solution really helps you get there um you know a lot of what we see with our analytic outcomes is instead of just giving customers pre-built set of con reports dashboards and the like give them the ability to essentially solve their own problems create dashboards from scratch uh either from a completely blank canvas or from maybe a set of Baseline templates that they can use to deliver successful analytical outputs let them create their own charts or metrics using a drag and drop no code uh Builder let them create their own custom filters actions workflows drill Downs uh all of those interactivities right let

them solve for their own problems within the solution which gives you the ability to not only create new value uh but also potentially if you're thinking about it from sort of the revenue generation perspective all of these tools offer opportunities to create more value for advanced users power users and really any users that are looking for a more robust set of self-service tools within your your software applications so um not only meet the demand but also opportunities that exist within offering robust self-service for for everybody all right let's talk about Trend number five which is thinking more along the lines of the underlying architecture and how it's shifting um

what we're seeing in the market is obviously a big shift from a single sort of cloud deployment to multicloud deployments and even many more hybrid and private Cloud deployment models uh 80% of companies in fact are incorporating multiple public clouds when it comes to their software Solutions uh and the majority are also using uh more than one even hybrid and private cloud and so what does that mean for your analytic solution well I think the key there is it just has to match to your software requirements so when you're looking at analytic tools um does it match to your SAS software development life cycle can it deploy

where you need it to deploy can it support your Dev staging production use cases um does it provide the tools to help you navigate all of those different environments publishing version management Administration and so architecture is something that should absolutely not be overlooked and when you're thinking about how you're going to meet the needs of your change ing software architectures look for tools and analytics architectures that match to what you're trying to accomplish with your SAS environments and your software development life cycles as well Trend six is kind of similar um except now we're talking about instead of just sort of single region single

zone what about global expansion internationalization and Global reach of SAS applications um more and more we're seeing SAS applications that we're working with have the need to serve customers across multiple geographies all over the globe uh which is in fact 80 85% of all business applications uh in in 2025 going to be sas-based operating in a hundred different countries and obviously the global SAS Market is not slowing down at all and so uh Global expansion if it's not already part of your road map or your expect expectations and plan uh it's something that obviously you you can start

thinking about and again just like with architectures uh understanding the tools that you work with should allow you to easily control and map to whatever internationalization and other outputs that you need to support users anywhere they are um it should be controllable for the uiux should be control able for the data and the content so everything from you know headers labels object names data points all that should be controllable from the uh the language and formatting and also how that's determined so is it something that you know the user determines for themselves is it something that's automatic um is it something that's individualized per report or per dashboard um thinking

about these things is really important as you look at how you can expand your reach globally particularly when it comes to the analytical outputs within your software applications and SAS environments so great Trend to keep an eye on and and how you're going to expand to match to the global needs of your software Trend number seven we'll talk about is really all about specialization uh again I think this trend is is more about what the expectations of workers are um you know as applications get more and more specialized and sophisticated uh the actual end users and and and workers within those applications are learning those new

skills and Technologies and a lot of that's in the realm of data and Analysis so 58% of essentially new job creation is related to analysis and data analysis uh within those organizations so um this is absolutely going to translate to more requirements and more requests for capabilities within your SAS software within your applications so thinking about how you're going to meet the needs of more specialized users more sophisticated users and more capable users is really important and I think this is absolutely an extension of the self-service points that we were making

earlier uh and the ability to offer different levels of capabilities to match the right skill sets of your customers whether that's a full self-service role or capability so an author who can create basically any analytic content and share that or maybe that's another layer of enhanced filtering or drill down and customization and personalization that gets created or maybe that's just a way to offer more data Access Data as a service via exports extending data so it integrates better with third-party tools or even thinking about how that wraps into the Automation and alerting capabilities of your SAS product um the key here is that specialization so how

are you going to map your product tiers to meet the needs of the end customers who have these more specialized needs with different roles within their organizations who are using your software uh and there's a lot of opportunities and analytics to kind of match to those different roles and requirements effectively Trend number eight let's talk a little bit about um Roi and um the interesting thing is you know not a lot of companies are really focused on Roi as part of their overall software strategy um you know only 46% of companies today are actually calculating the ROI of their it Investments after

they complete those projects and I think the trend that we're seeing is um this number is going to be going up a lot um software development teams um needing to show value and needing to show that what they're building what they're working on does have meaningful Roi for the the business uh and so being able to track and map sort of the ROI of everything is going to become increasingly important particularly for the any new initiatives that you choose to start around data or around analytics within your software Solutions so essentially what we recommend here is just think about all of the new Roi opportunities that an

analytics uh platform or analytics layer can afford and create for you as part of your overall software strategy um we've talked about you know the ability to offer different modules and add-ons um that's just one way you can consider Roi when it comes to analytics so new features equal new add-on modules equal new Revenue opportunities but what what about just things like data expansion we had the trend where we're looking at this huge explosion of data and now unstructured semi-structured data um that becomes a great Roi Revenue generating opportunity to expand on data size or data scale um and and use that to generate uh

meaningful new revenue streams as well um the other opportunity is um thinking about kind of that consolidation side of the analytics experience we saw that chart earlier the the the diagram earlier where kind of with Qrvey where everything's all-in-one versus all these external tools and services that you'd have to sort of spend time on learn become experts in and also pay for um so being able to consolidate all of that is not the revenue generating opportunity but the cost reduction opportunity uh for again generating meaningful Roi within your uh SAS business and within your analytics outcomes within that uh SAS development experience and then of course all those different use cases

whether it's self-service automation data collection data as a service those all present opportunities for new revenue streams new Roi within your applications so think about how that might translate to successful uh Revenue generating within your analytics outputs all right Trend number nine uh consolidation um consolidation is really a big Trend in the industry um in fact the average number of SAS products that companies are using is going down but they're using those products more and more uh and so a lot of companies or a lot of products are coming together and if you're part of a business or maybe even in your SAS company you've acquired

product or you started bringing together data from other products into your product as well these are great opportunities to now deliver um analytical and data analytics on top of those sort of multiple different products that you're working with and so think about analytics strategy that gives you opportunities to consolidate across multiple different products bring data together blend it join it combine it from multiple applications and sources and now you can your product teams can look at analytics as kind of the bridge between multiple applications so if you've recently acquired applications or your customers are just

expecting that more of their application data is combined and and available in a single place um there's a lot of great opportunities to kind of bring that data together and use the analytics layer as the way to consolidate across those different data sources and and services or applications directly so new opportunity exist as part of this kind of overall consolidation Trend to blend things together together and our last Trend um I I don't think anybody's any stranger to security needs and things like data privacy um but that's absolutely something that you know we see as kind of non-negotiable obviously most businesses agree as

94% um you know have to absolutely make sure that customers data is protected um and not just protected but um absolutely only exposed to the folks and the users and the roles of users who need to see the data that that they have access to so it's not just about protecting tenant data but even within tenants making sure that the users are only seeing the data that they would have access to are supposed to have access to and that's something that absolutely has to be part of your analytic solution and whatever tools that you use have to support the right options for data management and data security and that includes everything from encryption for data in transit and at rest that includes

opportunities for record level column level object level Security Options that includes making sure that your data isn't going somewhere external um and and if you're using self-hosted solution making sure that you have control over your customer's data and then of course when we talk about multi-tenant logic it has to cover all of those security scenarios including not forcing you to duplicate user information roll information and all of that type of logic so that it can all be managed and secured in the best fashion for your overall data privacy and security strategy within your business all right so those are our

Trends and thanks for taking the time to uh join us on our webinar talking about those top 10 Trends um I think again a lot of those Trends are really about how can you create the right types of value for your customers within the analytics modules or layers that you offer within your your product Suites or your SAS Solutions and so one of the things that you know we'd love to work with you on at Qrvey is um a free analytics assessment you can book a demo with us and uh we can review maybe what your current state of analytics looks like today and provide the right types of recommendations to move forward uh we

can also help you with that roadmap side of things so we talked about all of these new opportunities whether it's self-service automation consolidation security all of these things can be part of the next set of road map features that you choose to launch and we do have our free roadmap guide for analytics how to roll it out how to plan for the right features the right timelines and how to build that consensus internally um to deliver the best possible outcomes for your customer so visit us uh at the URL and uh book that assessment and uh hopefully we'll be in touch but thanks everybody for your participation today and we hope to see you on the next one take care