Posted In:SaaS Archives - AppFerret
The CRM market serving the large enterprise is mature. The market has consolidated in the past five years. For example, Oracle has built its customer experience portfolio primarily by acquisition. SAP, like Oracle, aims to support end-to-end customer experiences and has made acquisitions — notably, Hybris in 2013 — to bolster its capabilities. Salesforce made a series of moves to strengthen the Service Cloud. It used this same tactic to broaden its CRM footprint with the acquisition of Demandware for eCommerce in 2016.
These acquisitions broaden and deepen the footprints of large vendors, but these vendors must spend time integrating acquired products, offering common user experiences as well as common business analyst and administrator tooling — priorities that can conflict with core feature development.
What this means is that these CRM vendors increasingly offer broader and deeper capabilities which bloat their footprint and increase their complexity with features that many users can’t leverage. At the same time, new point solution vendors are popping up at an unprecedented rate and are delivering modern interfaces and mobile-first strategies that address specific business problems such as sales performance management, lead to revenue management, and digital customer experience.
The breadth and depth of CRM capabilities available from vendor solutions makes it increasingly challenging to be confident of your CRM choice. In the Forrester Wave: CRM Suites For Enterprise Organizations, Q4 2016. we pinpoint the strengths of leading vendors that offer solutions suitable for enterprise CRM teams. Here are some of our key findings:
- The shift to software-as-a-service (SaaS) is well underway. Forrester Data shows that 1/3 enterprises are using SaaS CRM, and another 1/3 complement their existing solutions with SaaS. We expect SaaS to become the primary deployment model for CRM and that newer SaaS solutions will replace most on-premises installations in the next five years.
- Intelligence takes center stage. Large organizations that manage huge volumes of data struggle to pinpoint optimal offers, discount levels, product bundles, and next best steps for customer engagement. They increasingly turn to analytics to uncover insight and prescribe the right action for the business user to take. Today, leading vendors offer a range of packaged capabilities to infuse decisioning in customer-facing interactions.
- Vendors increasingly invest in vertical editions. Horizontal CRM can only take you so far, as different industries have different requirements for engaging with customers. CRM vendors increasingly offer solutions — templates, common process flows, data model extensions, and UI labels — pertinent to specific industries.
- Customer success rises to the top. In a mature market, you have to dig deep to find real differences between vendor offerings. CRM success depends on the right choice of consulting partners to implement and integrate your solution. CRM vendors are maturing their consulting services, deeply investing in growing regional and global strategic services partners, and investing in customer success to properly onboard customers and actively manage customer relationships. This preserves a company’s revenue stream by reducing churn, expands revenue by increasing customer lifetime value, and can influence new sales via customer advocacy efforts.
Original article here.
Operator and vendor revenues across the main cloud services and infrastructure market segments hit $148 billion (£120.5bn) in 2016 growing at 25% annually, according to the latest note from analyst firm Synergy Research.
Infrastructure as a service (IaaS) and platform as a service (PaaS) experienced the highest growth rates at 53%, followed by hosted private cloud infrastructure services, at 35%, and enterprise SaaS, at 34%. Amazon Web Services (AWS) and Microsoft lead the way in IaaS and PaaS, with IBM and Rackspace on top for hosted private cloud.
In the four quarters ending September (Q3) 2016, total spend on hardware and software to build cloud infrastructure exceeded $65bn, according to the researchers. Spend on private cloud accounts for more than half of the overall total, but public cloud spend is growing much more rapidly. The note also argues unified comms as a service (UCaaS) is growing ‘steadily’.
“We tagged 2015 as the year when cloud became mainstream and I’d say that 2016 is the year that cloud started to dominate many IT market segments,” said Jeremy Duke, Synergy Research Group founder and chief analyst in a statement. “Major barriers to cloud adoption are now almost a thing of the past, especially on the public cloud side.
“Cloud technologies are now generating massive revenues for technology vendors and cloud service providers and yet there are still many years of strong growth ahead,” Duke added.
The most recent examination of the cloud infrastructure market by Synergy back in August argued AWS, Microsoft, IBM and Google continue to grow more quickly than their smaller competitors and, between them, own more than half of the global cloud infrastructure service market.
Original article here.
The end of year or beginning of year is always a time when we see many predictions and forecasts for the year ahead. We often publish a selection of these to show how tech-based innovation and economic development will be impacted by the major trends.
A number of trends reports and articles have bene published – ranging from investment houses, to research firms, and even innovation agencies. In this article we present headlines and highlights of some of these trends – from Gartner, GP Bullhound, Nesta and Ovum.
Artificial intelligence will have the greatest impact
GP Bullhound released its 52-page research report, Technology Predictions 2017, which says artificial intelligence (AI) is poised to have the greatest impact on the global technology sector. It will experience widespread consumer adoption, particularly as virtual personal assistants such as Apple Siri and Amazon Alexa grow in popularity as well as automation of repetitive data-driven tasks within enterprises.
Online streaming and e-sports are also significant market opportunities in 2017 and there will be a marked growth in the development of content for VR/AR platforms. Meanwhile, automated vehicles and fintech will pose longer-term growth prospects for investors.
The report also examines the growth of Europe’s unicorn companies. It highlights the potential for several firms to reach a $10 billion valuation and become ‘decacorns’, including BlaBlaCar, Farfetch, and HelloFresh.
Alec Dafferner, partner, GP Bullhound, commented, “The technology sector has faced up to significant challenges in 2016, from political instability through to greater scrutiny of unicorns. This resilience and the continued growth of the industry demonstrate that there remain vast opportunities for investors and entrepreneurs.”
Big data and machine learning will be disruptors
Advisory firm Ovum says big data continues to be the fastest-growing segment of the information management software market. It estimates the big data market will grow from $1.7bn in 2016 to $9.4bn by 2020, comprising 10 percent of the overall market for information management tooling. Its 2017 Trends to Watch: Big Data report highlights that while the breakout use case for big data in 2017 will be streaming, machine learning will be the factor that disrupts the landscape the most.
Key 2017 trends:
- Machine learning will be the biggest disruptor for big data analytics in 2017.
- Making data science a team sport will become a top priority.
- IoT use cases will push real-time streaming analytics to the front burner.
- The cloud will sharpen Hadoop-Spark ‘co-opetition’.
- Security and data preparation will drive data lake governance.
Intelligence, digital and mesh
In October, Gartner issued its top 10 strategic technology trends for 2017, and recently outlined the key themes – intelligent, digital, and mesh – in a webinar. It said that autonomous cars and drone transport will have growing importance in the year ahead, alongside VR and AR.
“It’s not about just the IoT, wearables, mobile devices, or PCs. It’s about all of that together,” said Cearley, according to hiddenwires magazine. “We need to put the person at the canter. Ask yourself what devices and service capabilities do they have available to them,” said David Cearley, vice president and Gartner fellow, on how ‘intelligence everywhere’ will put the consumer in charge.
“We need to then look at how you can deliver capabilities across multiple devices to deliver value. We want systems that shift from people adapting to technology to having technology and applications adapt to people. Instead of using forms or screens, I tell the chatbot what I want to do. It’s up to the intelligence built into that system to figure out how to execute that.”
Gartner’s view is that the following will be the key trends for 2017:
- Artificial intelligence (AI) and machine learning: systems that learn, predict, adapt and potentially operate autonomously.
- Intelligent apps: using AI, there will be three areas of focus — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces.
- Intelligent things, as they evolve, will shift from stand-alone IoT devices to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks.
- Virtual and augmented reality: VR can be used for training scenarios and remote experiences. AR will enable businesses to overlay graphics onto real-world objects, such as hidden wires on the image of a wall.
- Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.
- Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry.
- Conversational systems will shift from a model where people adapt to computers to one where the computer ‘hears’ and adapts to a person’s desired outcome.
- Mesh and app service architecture is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs (application programming interfaces) and events to deliver modular, flexible and dynamic solutions.
- Digital technology platforms: every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the internet of things and business ecosystems.
- Adaptive security architecture: multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.
The real-world vision of these tech trends
UK innovation agency Nesta also offers a vision for the year ahead, a mix of the plausible and the more aspirational, based on real-world examples of areas that will be impacted by these tech trends:
- Computer says no: the backlash: the next big technological controversy will be about algorithms and machine learning, which increasingly make decisions that affect our daily lives; in the coming year, the backlash against algorithmic decisions will begin in earnest, with technologists being forced to confront the effects of aspects like fake news, or other events caused directly or indirectly by the results of these algorithms.
- The Splinternet: 2016’s seismic political events and the growth of domestic and geopolitical tensions, means governments will become wary of the internet’s influence, and countries around the world could pull the plug on the open, global internet.
- A new artistic approach to virtual reality: as artists blur the boundaries between real and virtual, the way we create and consume art will be transformed.
- Blockchain powers a personal data revolution: there is growing unease at the way many companies like Amazon, Facebook and Google require or encourage users to give up significant control of their personal information; 2017 will be the year when the blockchain-based hardware, software and business models that offer a viable alternative reach maturity, ensuring that it is not just companies but individuals who can get real value from their personal data.
- Next generation social movements for health: we’ll see more people uniting to fight for better health and care, enabled by digital technology, and potentially leading to stronger engagement with the system; technology will also help new social movements to easily share skills, advice and ideas, building on models like Crohnology where people with Crohn’s disease can connect around the world to develop evidence bases and take charge of their own health.
- Vegetarian food gets bloodthirsty: the past few years have seen growing demand for plant-based food to mimic meat; the rising cost of meat production (expected to hit $5.2 billion by 2020) will drive kitchens and laboratories around the world to create a new wave of ‘plant butchers, who develop vegan-friendly meat substitutes that would fool even the most hardened carnivore.
- Lifelong learners: adult education will move from the bottom to the top of the policy agenda, driven by the winds of automation eliminating many jobs from manufacturing to services and the professions; adult skills will be the keyword.
- Classroom conundrums, tackled together: there will be a future-focused rethink of mainstream education, with collaborative problem solving skills leading the charge, in order to develop skills beyond just coding – such as creativity, dexterity and social intelligence, and the ability to solve non-routine problems.
- The rise of the armchair volunteer: volunteering from home will become just like working from home, and we’ll even start ‘donating’ some of our everyday data to citizen science to improve society as well; an example of this trend was when British Red Cross volunteers created maps of the Ebola crisis in remote locations from home.
It’s clear that there is an expectation that the use of artificial intelligence and machine learning platforms will proliferate in 2017 across multiple business, social and government spheres. This will be supported with advanced tools and capabilities like virtual reality and augmented reality. Together, there will be more networks of connected devices, hardware, and data sets to enable collaborative efforts in areas ranging from health to education and charity. The Nesta report also suggests that there could be a reality check, with a possible backlash against the open internet and the widespread use of personal data.
Original article here.
Are sites, applications, and IT infrastructures leaving the LAMP stack (Linux, Apache, MySQL, PHP) behind? How have the cloud and service-oriented, modular architectures facilitated the shift to a modern software stack?
As more engineers and startups are asking the question “Is the LAMP stack dead?”—on which the jury is still out—let’s take a look at “site modernization,” the rise of cloud-based services, and the other ever-changing building blocks of back-end technology.
From the LAMP Era to the Cloud
Stackshare.io recently published its findings about the most popular components in many tech companies’ software stacks these days—stacks that are better described as “ecosystems” due to their integrated, interconnected array of modular components, software-as-a-service (SaaS) providers, and open-source tools, many of which are cloud-based.
It’s an interesting shift. Traditional software stacks used to be pretty cut and dry. Acronyms like LAMP, WAMP, and MEAN neatly described a mix of onsite databases, servers, and operating systems built with server-side scripts and frameworks. When these systems grow too complex, though, the productivity they enable can be quickly eclipsed by the effort it takes to maintain them. This is up for debate, though, and anything that’s built well from the ground up should be sturdy and scalable. However, a more modular stack approach still prompted many to make the shift.
A shift in the software stack status quo?
But modularity is not without its complexities, and it’s also not for everyone. SaaS, mobile, and cloud-computing companies are more likely to take a distributed approach, while financial, healthcare, big data, and e-commerce organizations are less likely to. With the right team, skills, and expectations, however, it can be a great fit.
What are some of the key drivers of this shift?
1. Continuous deployment
What’s the benefit of continuous deployment? Shorter concept-to-market development cycles that allow businesses to give customers new features faster, or adjust to what’s happening with traffic.
It’s possible to continuously deploy with a monolith architecture, but certain organizations are finding this easier to do beyond a LAMP-style architecture. Having autonomous microservices allows companies to deploy in chunks continuously, without dependencies and the risk of one failure causing another related failure. Tools like GitHub, Amazon EC2, and Heroku allow teams to continuously deploy software, for example, in an Agile sprint-style workflow.
2. The cloud is creating a new foundation
Cloud providers have completely shaken up the LAMP paradigm. Providers like Amazon Web Services (AWS) are creating entirely new foundations with cloud-based modules that don’t require constant attention, upgrades, and fixes. Whereas stacks used to comprise a language (Perl, Python, or PHP), a database (MySQL), a server, operating system, application servers, and middleware, now there are cloud modules, APIs, and microservices taking their place.
3. Integration is simplified
Tools need to work together, and thanks to APIs and modular services, they can—and without a lot of hassle. Customer service platforms need to integrate with email and databases, automatically. Many of the new generation of software solutions not only work well together, they build on one another and can become incredibly powerful when paired up, for example, Salesforce’s integrated SaaS.
4. Elasticity and affordable scalability
Cloud-based servers, databases, email, and data processing allow companies to rapidly scale up—something you can learn more in this Intro to Cloud Bursting article. Rather than provision more hardware and more time (and space) that it takes to set that hardware up, companies can purchase more space in the cloud on demand. This makes it easier to ramp up data processing. AWS really excels here, and is a top choice for companies like Upwork, Netflix, Adobe and Comcast have built their stacks with its cloud-based tools.
For areas like customer service, testing, analytics, and big data processing, modular components and services also rise to the occasion when demand spikes.
5. Flexibility and customization
The beauty of many of these platforms is that they come ready to use out the box—but with lots of room to tweak things to suit your needs. Because the parts are autonomous, you also have the flexibility to mix and match your choice of technologies—whether those are different programming languages or frameworks and databases that are particularly well-suited to certain apps or projects.
Another thing many organizations love is the ability to swap out one component for another without a lot of back-end reengineering. It is possible to replace parts in a monolith architecture, but for companies that need to get systems up and running fast—and anticipate a spike in growth or a lack of resources—modular components make it easy to swap out one for another. Rather than trying to adapt legacy technology for new purposes, companies are beginning to build, deploy, and run applications in the cloud.
6. Real-time communication and collaboration
Everyone wants to stay connected and communicate—especially companies with distributed engineering teams. Apps that let companies communicate internally and share updates, information, and more are some of the most important parts of modern software stacks. Here’s where a chat app like HipChat comes in, and other software like Atlassian’s JIRA, Confluence, Google Apps, Trello, and Basecamp. Having tools like these helps keep everyone on the same page, no matter what time zone they’re in.
7. Divvying up work between larger teams and distributed teams
By moving architectures to distributed systems, it’s important to remember that the more complicated a system is, the more a team will have to keep up with a new set of challenges: things that come along with cloud-based systems like failures, eventual consistency, and monitoring. Moving away from the LAMP-style stack is as much a technical change as it is a cultural one; be sure you’re engaging MEAN stack engineers and DevOps professionals who are skilled with this new breed of stack.
So what are the main platforms shaking up the stack landscape?
The Stackshare study dubbed this new generation of tech companies leaving LAMP behind as “GECS companies”—named for their predominant use of GitHub, Amazon EC2, and Slack, although there are many same-but-different tools like these three platforms.
Upwork has moved its stack to AWS, a shift that the Upwork engineering team is documenting on the Upwork blog. These new platforms offer startups and other businesses more democratization of options—with platforms, cloud-based servers, programming languages, and frameworks that can be combined to suit their specific needs.
- Ruby and Python also dominate the new back-end stack, along with Node.js.
- Amazon Web Services (AWS): The AWS cloud-based suite of products is the new foundation for many organizations, offering everything from databases and developer tools to analytics, mobile and IoT support, and networking.
- Computing platforms: Amazon EC2, Heroku, and Microsoft Azure
- Databases: PostgreSQL, with some MongoDB and MySQL.
The good news? There’s no shortage of Amazon Web Services pros, freelance DevOps engineers, and freelance data scientists who are skilled in all of these newer platforms and technologies and poised to help companies get new, cloud-based stacks up and running.
Read more at http://www.business2community.com/brandviews/upwork/cloud-computing-changing-software-stack-01644544#kEgMIdXIW7Q0ZpOt.99
The cloud computing markets are growing at a rapid pace. People prefer to incorporate cloud technology in their day to day work because of its convenience. According to the reports of IDC, public cloud spending is expected to grow to more than $195 billion in 2020 from $96.5 billion in 2016.
A senior SaaS executive once told me, “Reports sell software.” In a top down sale, that’s absolutely true. The CEO wants better predictability of bookings, so she’ll buy a CRM tool to gather the data. Classically, software has been built for that mantra.
First, a company buys a database. The sales people, marketers or customer care staff continue working as normal. But after the purchase, these teams are burdened with an additional step of updating the database when they’ve finished their work, so a report can be generated.
But this design has an agency problem. The employees investing the marginal effort see very little gain. This agency problem challenges the effectiveness of the software in three ways.
First, managers must motivate employees to update the database. Second, since employees report data retroactively, the database is always out of date, undermining the accuracy of the reports. Third, the benefit of the software to employees is only visible months or years after filling up the database, when an employee can review the history of a customer interaction for example.
In bottoms up sales, workflow sells software. And new SaaS companies who aim to displace incumbent systems of record will architect their products in a radically different way. They will be event-driven SaaS companies.
Event driven SaaS products consume events from data sources, data sources like social media, news, analytics data, marketing data, customer support data, sales data. All of these events are ingested via API and committed to the database. Day one, these new systems of record are filling themselves with data.
Using this information, they prioritize and inform work to aid their teams be more effective. That can be by prioritizing which customers to speak with, automatically answering customer support queries or any number of things not yet invented.
Critically, there’s a feedback loop. The users’ actions are themselves events that feed back into the database. Separately, the system generates a similar report.
Event-driven SaaS products mitigate and ideally eliminate the agency problem of classic software. Users benefit directly from using it. The reporting is a by-product of an optimized workflow, and coincidentally is much more accurate than a classical system.
This agency problem the heart of the adoption challenges of classical software deployments, and in particular of the dominant systems of record in the market today. The next generation of multi-billion dollar SaaS platforms, the startups who will displace incumbents, will do it with event-driven architectures and optimized workflows.
Original article here.