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BIAMI.IO offers Intelligent Automation solutions to build intelligent business process driven software, platforms and robots. Based on its own technology, an enterprise-ready automation framework, the company offers solutions in four areas:
Intelligent Automation for the People – Software and solutions for individuals to automate their daily tasks. Users can create their individual automated business processes using BIAMI DEV, a free and open source software or use BIAMI Personal Cloud, a free cloud service for non-commercial use.
Enterprise Intelligent Automation Cloud Platform – Software and solutions for business customers to build their own intelligent and automated solutions at scale in public, private or hybrid cloud deployment. Automation clusters built with BIAMI Enterprise Edition software include additional solutions like BIAMI Resource Management and BIAMI Performance Management to build complex solutions in elastic and scalable infrastructure and meet automation SLA.
Enterprise Intelligent Automation Transformation – Horizontal or industry-specific solution templates for building the best intelligent automation solutions in the market which decreases the amount of time necessary for successful automation implementation.
Embedded Intelligent Automation – Software, solutions and hardware designs, and appliances that deliver autonomous intelligent automation solutions as a part of a wider proposition of its customers.
BIAMI.IO’s mission is to increase the
quality of life through automation transformations where everyone is able to raise the quality, reach and efficiency of what they do with easy to build and manage intelligent automation solutions.
A Charismatic Leader
Marcin Kierdelewicz, a veteran in the software industry founded chúng tôi in 2023 after working at automation framework software product development in
initial years. From
experience with SAP, Marcin gained familiarity to build and grow software businesses from startups to over
valuation. BIAMI.IO’s founding team had half-a-dozen people who worked together for many years with vision to build the best automation proposition on the market. BIAMI DEV is the only open source enterprise framework and BIAMI is the only proposition in the market that lets non-technical people describe automation process and collaborate with others in order to share the experience and improve the quality of intelligent automation processes built.
Excelling in Open Source Collaborations
Intelligent Automation and RPA are the core of BIAMI.IO’s offerings. The unique part of
proposition in the market is its open source collaboration where BIAMI and its customers share automation processes on platforms like Github to collaborate with others without a need to share the secret sauce. This type of collaboration lets everyone bring skills that are needed and deliver the best automation solutions in the market.
Long term strategy for BIAMI includes elements of Artificial Intelligence (AI), Machine Learning (ML) and Natural Language Processing (NLP) which are a core part of its future products release including an intelligent chatbot.
Navigating Success with AI, ML, NLP and Chatbots
Collaborative Partnerships that Drive Innovation
In intelligent automation space, almost everything that people talk about is innovative. Automation is the future and is only about how easy it is to build automation solutions in order to increase the automation adoption. chúng tôi is the only solution on the market that does not require developers to automate business processes. The company’s first key alliances include top 3 cloud vendors where it has worked with them to build a better experience, collaboration and elastic automation infrastructure. chúng tôi has also partnered with many system
companies to deliver consulting and implementation services while focusing on core proposition development and customer support.
Fostering Automation Framework
Marcin usually does not put all the things in one bucket. Intelligent Automation is the
but reality is that all of the current RPA leading vendors including UiPath, BluePrism and Automation Anywhere don’t offer very intelligent automation solutions. They’re focusing on one and the same area which makes it more and more technical. BIAMI.IO’s approach is different. From the very beginning, the company had its automation framework that can be extended adding more and more value with every project. RPA is only a part of what the team
can do at chúng tôi and the company’s approach to collaborate and focus on working with business managers makes it unique in the
works and the outcome the customers get. Marcin believes that AI, NLP and Chatbot will constitute a proposition of every vendor and it’s only a matter of time when people see that. The difference will be in the details and what people can do with every vendor’s AI, NLP and Chatbot proposition. That will define a different positioning of the
the market in the future.
Addressing Capacity Building Challenges
BIAMI.IO is relatively a new company in the market. It has notable achievements and great customer success stories in the commercial market, including delivering a significant part of the business for one of the Telco’s in Europe with over 5 million services provisioned in over 2 years with zero downtime. That was achieved only because the company was able to check if the resources were available before the automation process kicked-off. The automation processes
managed at every stage with the possibility to roll-back or completely restart the process if there was any potential failure.
BIAMI.IO got a complex marketplace order processing automation for one of the leading online retailers where the company remarkably decreased the time and resources needed to manage multi-vendor orders.
An Ambitious Roadmap for Future Expansion
Current RPA vendor
holds the world record for the “Year on Year Growth” with results that
never achieved before. Not even close. And in Marcin’s opinion, this is just the beginning of what chúng tôi is going to see. Automation will help business to grow and scale faster than ever before. For everyone it means that while Amazon is the biggest company in the world and not many people would predict that such a tech giant could be built within such a short period of time. Reality is that it takes less time to build global successful companies in future and that becomes a standard.
You're reading Biami.io: Harnessing Automation To Build Intelligent Business Driven Solutions
Courses in the NYU Stern MS in Business Analytics program focus around the domain-specific areas such as analytics strategy, marketing, optimization, and revenue management. Students tackle examples of data-driven decision-making in firms and consider the strategic, policy, and economic implications of business analytics. NYU Stern MS in Business Analytics program additionally includes a course on data privacy and ethics, which is a pressing issue related to business analytics, and of growing importance.Exceptional Business Analytics Program Bringing Analytics Education to Executives
NYU Stern’s MS in Business Analytics program is uniquely positioned for an executive audience. The average age of the students is 37 and the average work experience is 12 years. NYU Stern MS in Business Analytics is a part-time program where students are working full-time and study part-time. Students taking the course come from different geographic regions and industries where each can share their perspective on how analytics is being used in their businesses. This diverse representation is intentional because, in an executive program like this, work experience is important. Students not only learn from the faculty but also learn from each other.Motivating Leadership and Global Faculty
NYU Stern’s Master of Science in Business Analytics program draws inspiration from its Global faculty who inspire students to lead data science careers worldwide. Roy Lee serves as Assistant Dean at New York University’s Stern School of Business, responsible for providing the strategic direction and oversight of the School’s Executive Programs (EP) group. The EP group serves as an innovation lab for NYU Stern, creating and developing high-quality degree and non-degree programs for experienced professionals that increase and diversify the School’s portfolio of offerings. In addition, Roy serves as the analytical lead working on a School-wide initiative to develop and foster NYU Stern’s internal data analytics capabilities.Adding Value to Analytics Delivery
“Our students gain a sense of confidence and credibility. Post-graduation, our students gain confidence by having technical capabilities to speak the language to understand how to work with data and become a translator of that information, or a disruptor of business thought and strategy in a positive and impactful way,” said Roy. They also now have the credibility of the NYU Stern degree, along with a specialized skill-set, where they can blend their business domain knowledge along with next-generation analytics to add increased value to their organizations.Peer to Peer Interaction
The learning from the MS in Business Analytics program extends beyond the classroom pedagogy. Specifically, students should choose a program where their peer group will be as important as the faculty who teach in the program. With NYU Stern MS in Business Analytics global program, students coming from different nationalities and diversity in a cohort leverage an opportunity to challenge their perspective and assumptions that they may have and this enlightens them to new ways of approaching data-related business problems faced across different industries, job functions and locations. The peer group at the college adds a depth to the learning experience, beyond the classroom through discussions and debates in-class, leading to intellectual, stimulating conversations and amazing learning experiences.Offering Practical Exposure for Industry Collaborations
The MS in Business Analytics Capstone is a team-based project in the program curriculum, which gives students the opportunity to demonstrate an understanding of the core competencies taught throughout and apply them to real business problems. Capstone projects use business analytics to address a specific strategic issue. All projects include data mining, modeling and/or other business analytics techniques learned in the program. Past projects range from improving operational efficiency in hospitals by using analytics, using HR analytics to predict talent acquisition and identifying drivers for workforce performance, and the development of an application for surge pricing models for electric vehicles.Analytics-Driven Organizations: The Way Forward
Business Team Collaboration: Effective For Information Gathering, But Hinders Creation Of Diverse Solutions
Collaboration Has Its Limits For creative problem solving, organizations still need some people who don’t directly work together, says business school prof Jesse Shore
Jesse Shore found that a high degree of collaboration helps in the information-gathering part of problem solving, but that it hinders the ability of the group to come up with diverse solutions. Photo by Jackie Ricciardi
Cubicles and closed doors are out. With collaboration the organizational mantra of our time, managers have transformed the modern office into a sea of open space, where groups of people solve problems together. Online, it’s all about maximizing connectivity and sharing within the social network. “Team communication for the 21st century—everyone has a transparent view of what’s going on,” promises Slack, one of an array of popular software programs designed to boost collaboration among groups in the workplace.
It turns out, though, that for creative problem solving, it still pays off to have some people in an organization who don’t directly work together. That is what Jesse Shore, an assistant professor of information systems at Boston University’s Questrom School of Business and an expert on communications, information, and connectivity, found in an October 2024 study. But don’t get Shore wrong. He isn’t suggesting that collaboration is a bad thing. His study, in fact, also demonstrates the benefits of collaboration and a high degree of connectedness among a group of people—or, to use the social science research term, clustering. It all depends on which part of the problem-solving process people are engaged in—the search for information or using the information to come up with solutions.
Shore and his co-authors, Ethan Bernstein, an assistant professor of leadership and organizational behavior at Harvard Business School, and David Lazer, a professor of political science and computer and information science at Northeastern University, write in their study that “clustering promotes exploration through information space but inhibits exploration through solution space.”
For their experiment, the researchers adapted a US Department of Defense (DOD) tool for conducting experiments on collaboration and information gathering and customized a 25-minute whodunit game: figuring out the who, what, when, and where of a pending terrorist attack. Some 400 undergraduate participants were divided into 16-person groups. Each group was organized into one of four networks, which ranged from highly clustered to minimally clustered. Those in the highly clustered communications networks were five percent more efficient in searching for unique facts or clues. But those who were not densely clustered came up with 17.5 percent more unique theories or solutions. The study, “Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces,” was funded by the DOD and the US Army Research Laboratory and published in Organization Science in September 2024.
“The research was just one experiment in a lab,” Steve Lohr wrote in a 2014 article about the study in the New York Times, “but it does point to the larger subject of striking a balance between connectedness and isolation in the digital age.”
BU Research sat down with Shore to talk about his study and about patterns of collaboration, clustering, network structures, and problem solving—and what he’s looking at next.BU Research: What was the goal of your study?
Shore: We were testing the effects of communications patterns on the success of organizations in solving problems. We were looking at whether they could both find diverse information and generate diverse interpretations of that information.Why were the clustered networks better at searching for information or clues?
The clustered network was more coordinated at the group level in finding unique information. There is something sort of natural to that. If you can observe what everyone in the team is doing, you’re not going to reproduce their work. You’ll say ‘I should work on something different, we’ll cover more territory.’What about the second phase of problem solving that you tested—the search for solutions?
When it comes to interpreting that information to come up with conclusions, coordinating might not necessarily be the best thing. If I see you’ve adopted a solution, I might simply copy yours.Is that human nature?
When more than one of your neighbors has adopted a solution, you see what’s known as social proof: ‘Everyone thinks this, so it must be true.’ In terms of thinking independently, it’s not the number of collaborators or the amount of communication that matters. It’s the pattern of communication ties that make up the network structure of the whole organization.What was new about this study in terms of research on networks?
We separated the part of problem solving that is about coming up with solutions from the part about the information gathering that are the building blocks for those solutions. Prior researchers hadn’t thought to do that when studying the effects of network structure on problem solving.Where do you hope people will go from here?
We want this information to be built on. Outside of the lab, it’s hard to disentangle the effect of network structures from a whole bunch of other things, such as the attributes of the individuals in the network or any number of important contextual variables that could have shaped the network in the first place. We wouldn’t say this gives you the complete solution for all real-world applications, but it gives you an insight—that the structure that helps one part of the problem-solving process might not be the structure to use for the other part of the problem-solving process. Where coordinated search for information is the goal, you might want to favor a clustered network structure. It will naturally be more efficient and coordinated. But a clustered pattern of ties can lead to homogeneity of interpretation and it’s not necessarily so good for the part where you want to generate diverse solutions.What can you tell us about how to navigate all this “high communications connectivity,” as you describe it?
The question is how to manage it. We’re adopting communications technologies at an extremely rapid rate, in a sort of breathless way. It can help us in many ways. It can also end up suppressing the diversity of experiences we have, the diversity of ways we understand information. I don’t think connectivity is reducing the diversity of information. I think we’re getting much more information. Just look at Wikipedia—people joke about it, but it’s becoming an amazing repository of diverse information. But what all this connectivity might not be consistent with is having diverse opinions about that information, drawing diverse conclusions, and coming up with creative applications to use in new settings.So what can we do to avoid homogeneous thinking in the networked world?
You can design your communications technologies to avoid that. That would definitely be a frontier for future work.Would you like to study that?
I would love to work on that.You’re working on two new studies, one using a network model to examine the international music trade, which is forthcoming in the journal Network Science, the other on Twitter and diversity of opinion. Can you tell us a little about what you’ve learned?
The first paper asks how markets for “information goods” come into being. Commodities, like coal or paper, may have a utilitarian value no matter where you go in the world, but an information good, like a song or a book, does not. There could be a huge market for a certain kind of music in one country and no market at all in another. So this study looked at how new markets for information goods come into being. I found that, historically, new markets for music formed when the potential exporter and the potential importer had both imported from the same third country in the past. The pattern of trade today influences demand for information goods tomorrow.
As for the Twitter paper, it’s currently under review, but we’re looking at whether social media really does support the polarization and echo chambers we hear about so much in the news. Our data allows us to get a broader look at those questions than previous studies have taken.
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The many ways technology has transformed our lives can be seen clearly in the ways we live, work, shop and communicate
Customers today are more likely to use online channels to complete their journeys than ever before. Gone are the days when customers were anxious about ordering online. Nowadays, many people are just as confident and trusting of websites as they are of heading into a physical store.
This isn’t just for impulsive, cheap purchases like fast fashion or consumer goods either. As online channels continue to become normalized, customers are also increasingly heading online to shop for higher ticket items too, such as cars and high-end electronics.
Download our Individual Member Resource – Website and e-commerce personalization guide
This guide is aimed at marketing managers involved with making the business case for personalization, looking to plan a personalization implementation or extend their use of personalization.
The many ways technology has transformed our lives can be seen clearly in the ways we live, work, shop and communicate. It’s become so deeply entwined with everyday life that it’s difficult to imagine going a day without technology.
With this in mind, it’s understandable that a lot of companies are now choosing to automate many of their processes, communications and marketing strategies. It falls in line with the modern consumers’ desire for all things digital, so it’s the next logical step towards improving customer experience, right?
Well, not exactly.
It’s true that digitalized processes are convenient and are generally well-received today, but automation simply cannot provide the attention to detail and the human-touch that customers still want.
But let’s also be realistic. It’s impossible to run a big company, or any company for that matter, without having some processes automated. In fact, customers now expect certain processes to be automated. For example, I’d hazard a guess that most customers expect order confirmation emails to be automated. After all, if the technology exists to make more processes more efficient, why not make the most of it?How do you strike the balance?
Like anything, automation and personalization only work effectively when they are well-balanced. Too much automation and your company seems inhuman, detached, and the customer lacks interest in your campaigns as they aren’t tailored to their needs. On the other hand, too much personalization can feel intrusive, overwhelming and just plain creepy.
To find out how to balance automation and personalization, let’s delve into three key parts of the customer journey, and why getting it right is so important to the ongoing relationship between a brand and its customers.Surprise and delight
A key benefit of automation is that it allows companies to deduce information about their customers and use the information to provide a better quality service. By knowing the preferences of customers on paper, companies can be more precise in their targeted marketing campaigns, which is something most modern consumers have now come to expect.
The problem is that humans don’t exist on paper; they’re real, three dimensional and, at times, contradictory. People want different things at different times, but consumers’ expectations for a great service remains incredibly high.
This means that in order to surprise and delight customers, the method must be tailored to their specific needs and delivered in a way that makes the customer feel special.
Automation can help businesses gather information about their customers quickly and effectively to help achieve this (provided they don’t take it too far- more on that later). The key thing to remember is that technology should be used to facilitate a better customer experience, not rip out human interaction entirely. Here’s a great example of how a restaurant surprised and delighted its most regular customers.Use automation to bring people together
The owner of the restaurant recognized a regular customer through beacon on an app as they walked through the front door. The owner could see from the customer’s previous order history that they always order the same starter, so without being prompted, the owner sends the waitress over to their table with their favourite starter on the house. The customer was thrilled and although the delivery of the surprise was highly personalized, it was made possible through an automated notification on a restaurant system.
In this instance, it would be impossible even for a human to get it right 100% of the time, but thanks to clever data collection and automation, the restaurant owner could be sure that the gift would be well received by the customer. It ensured that they were made to feel appreciated and valued.
Another great example of how a company used personalized messaging to surprise and delight customers is Sainsbury’s.
Sainsbury’s is a UK-based supermarket chain, which is known for its forward-thinking approach to technology. It was the first European retailer to introduce self-service machines in all of its stores and it has recently opened the first ever no-till store.
The team at Sainsbury’s went one step further in 2023 with their ‘The Time It’s Ultra Personalized!’ campaign. By using smartphone location data, they were able to offer customers personalized offers and promotions through their phones as they were walking around the store. Not only did it help to promote in-store offers, but it also provided valuable insight into the way customers navigate the stores. This helps Sainsbury’s to make better merchandising decisions and improve its in-store customer experience.Handling customer queries
In an effort to streamline customer services processes and reduce contact centre wait times, many companies are increasingly leaning towards automation. The most obvious example of this can be seen with the rise of chatbots, but other forms of AI such as IVR (Interactive Voice Response) are also being used to communicate with customers directly.
This isn’t such a bad thing when it’s being used properly. After all, big companies have a huge volume of customer cases they need to manage on a daily basis, so it makes sense to have a system in place that can sort through the queries and send them over to the correct department.
But here’s the problem: whilst people nowadays expect high efficiency and speed, they also expect a high-quality customer experience. Automation works well for triaging queries, but it simply isn’t robust enough yet to handle a complex conversation, which means that this can cause more harm than good for the customer.
Ultimately, if a customer is trying to resolve an issue with a company and the assigned help is an automated bot that can’t understand them or help them properly, this will just infuriate the customer and increase case resolution times.Truly personalized support can only come from humans
Automated solutions like chatbots can work well for responding to simple queries and FAQs. In fact, this can be an optimal setup, as it alleviates resources from the customer service team who can, therefore, spend more time talking with customers and managing more complex enquiries.
But there are also more nuanced ways to balance the two. Incorporating a live chat feature on your website can enable human communication between agents and customers, meaning the customer receives high-quality answers to their questions quickly.
It also means that customers can engage in more meaningful conversations with agents as they journey through a website together. The support is personal and tailored, but technology makes the whole experience more efficient for both the company and the customer.
Remember, people usually contact customer services for one of two reasons: they have a problem that needs fixing, or they need more information about something. Customers want to feel supported in both of these scenarios, and the best way of ensuring that is by making it as easy as possible for them to have a real conversation with another person.News updates and promotions
There are times when personalization is neither necessary nor efficient, such as when sending out important company news updates to customers, offers or promotions. It’s impossible for any company to individually send every customer an email containing a personalized coupon, for example.
Similarly, it’s not the most effective strategy to send everyone on the mailing list the exact same promotion or offers, as customers’ interests vary greatly depending on the products they’re looking to purchase.
Of course, some could argue that sending over offers or promotions to customers should always be personalized to some extent as it encourages customers to buy, and there’s some truth in that.
For example, if I was shopping for a summer dress, it makes sense that the clothing company I was browsing on would send me a discount code for 30% off summer dresses because they know from their website history that this is highly relevant to me. In fact, I daresay I’ve received many emails like this… and many have worked.
But there’s a line.
Hyper-personalized marketing tactics can sometimes go too far, making customers feel more creeped out than impressed. Problems with personalization can arise when brands don’t pay enough attention to the people they’re targeting and how their targets might make the customer feel.
A particularly creepy example of this is the man in assisted living who was sent a personalized Christmas hamper from the local mortuary. Not exactly the best Christmas present, I think we can all agree.
Another example of this is the infamous Target story, where a distressed father angrily called up his local Target store after they had sent his teenaged daughter pregnancy-related goods coupons. Turns out, their prediction was completely correct.
Customers are willing to share their data with brands they trust, so it’s important not to break that trust. Algorithms and customer data can be used effectively to improve the customer’s experience, but beware of losing sight of the line in the sand. Taking personalization too far can become unnerving or alarming to your customers, which can create a negative brand image and deter them from your services.Just remember, the most important thing is CS
To avoid confusion, when I say CS, I’m not talking about customer service. I’m talking about common sense.
When figuring out how to balance automation and personalization, remember that you’re not just a marketer, you are also a consumer, so apply some common sense to the situation. Take a step back from your campaigns and consider how you would feel if you were on the receiving end of the targeted message.
Hold a mirror up to your campaigns and have a frank discussion about them. Is it too personalized – would you wonder why and how the company got your personal information? Is it overly automated and do you think your customers would feel isolated if they had a problem or need help?
There’s a simple way to help you achieve the best balance between automation and personalization. It’s easy to get swept away with the tide of the latest trends and technology to help you dazzle customers and hit your targets, but it’s important to make sure that your use of automation and personalization are logical and always put your customer’s experience first.
MicroStrategy is a worldwide leader in enterprise analytics and mobility software. A pioneer in the business intelligence and analytics space, MicroStrategy delivers innovative software that empowers business users to make better decisions and transform the way they work. MicroStrategy provides organizations with world-class software and expert services to deploy customized applications that accelerate organizations on their path to becoming an Intelligent Enterprise.
MicroStrategy’s mission is to provide businesses with the technology and technique needed to become an Intelligent Enterprise—the ultimate data-driven organization. The company’s vision is that the Intelligent Enterprise anticipates challenges and opportunities and turns them into profit and growth. MicroStrategy delivers a single version of the truth and agility, scalability and speed, AI and data discovery, enterprise analytics and mobility solutions. It connects to any data and distributes reports to thousands of users. An Intelligent Enterprise goes beyond business intelligence, delivering transformative insight to every user, constituent, and partner. The more organizations can become Intelligent Enterprises, the more productive and effective the business intelligence community will be.
The Dynamic Leader and Innovator
Michael J. Saylor is the President, Chairman & CEO of MicroStrategy. He has served as Chairman of the Board of Directors and CEO since founding MicroStrategy in November 1989 and has served as President since January 2024, a position he previously held from November 1989 to November 2000 and from January 2005 to October 2012.
In 1989 at the age of 24, Saylor combined his passions for technology, business, and the use of computer simulations to launch MicroStrategy. The company was founded on his vision of helping enterprises deliver intelligence everywhere. By harnessing the power of graphical operating systems and client-server computing and pioneering a new approach to business intelligence called relational online analytical processing (ROLAP), the company grew steadily, going public in 1998 (NASDAQ: MSTR). Under his leadership, MicroStrategy has emerged as a global leader in enterprise analytics and mobility software, serving thousands of institutions and organizations around the world.
Saylor is a named inventor on more than 40 patents. In addition to being credited as the inventor of relational analytics, he led MicroStrategy into the fields of web analytics, distributed analytics, mobile analytics, cloud computing, mobile identity, and IoT. He was also the creator and founder of chúng tôi (NASDAQ: ALRM), one of the first home automation and security companies, and chúng tôi (sold to Genesys Telecommunications Laboratories for US$110 million in 2013), one of the first cloud-based interactive voice response service providers.
Saylor is the author of the book “The Mobile Wave: How Mobile Intelligence Will Change Everything”, published by Perseus Books in 2012. The book anticipated the impact of mobile, cloud, and social networks on worldwide political and economic development, along with the rise of Apple, Amazon, Facebook, and Google as transnational technology leaders that would destabilize the status quo across most industrial and political domains. The Mobile Wave appeared on both The New York Times and The Wall Street Journal Best Seller lists.
In 1999, Saylor established The Saylor Foundation, which has donated millions to philanthropic causes including children’s health, refugee relief, education, environmental conservation, and support for the arts. The foundation runs the Saylor Academy (Saylor.org), which offers free college education and continuing professional development courses to students worldwide. To date, it has provided free educational services to more than 225,000 students. In 2024, 2024 and 2023, Saylor participated in the Forbes 400 Summit on Philanthropy.
Enabling Data-Driven Business Transformation
MicroStrategy works with a network of certified partners who offer some of the most innovative technologies to build analytics platforms. The partners help drive the company’s mission to empower more data-driven organizations forward. The MicroStrategy platform is extensible and fully customizable—providing access to databases, ETL tools, and big data solutions that seamlessly connect to other enterprise data architectures. The company’s partners are experts in implementing analytics and mobility applications that help modern businesses solve critical business challenges.
Earning Remarkable Recognition
MicroStrategy has been recognized by esteemed organizations globally for innovation and business excellence. Below are a few of the significant achievements.
• Named as the Sole Challenger in Gartner’s 2023 Magic Quadrant for Analytics and Business Intelligence Platforms
• MicroStrategy’s Customer Sumitomo Rubber North America won Ventana Research’s 2023 Leadership Award for Digital Technology by using MicroStrategy Mobile
• MicroStrategy’s Customer Houghton Mifflin Harcourt won 2024 Ventana Research Technology Innovation Leadership Award for embracing MicroStrategy Mobile
Business Intelligence: The Future is Intelligent Enterprises
The company’s perspective on the business intelligence space is centered around two main pillars: 1. the need for a single form of truth and, 2. the idea of “intelligence everywhere”—where business intelligence and analytics can impact every member of an organization.
MicroStrategy finds that many companies face the challenge of establishing a single record of data. When working with various sets of data or KPIs throughout the company, it’s difficult to know which numbers are accurate and reliable. MicroStrategy believes business intelligence should enable organizations to consolidate their data into a centralized platform, establishing a “single version of truth.”
The company also operates on the notion that business intelligence should empower every member of the enterprise, regardless of technical skill or area of focus, to access and utilize data analytics. With its user-friendly, self-service-focused platform, MicroStrategy allows data to informed decision-making at every level of the organization, transforming it into an Intelligent Enterprise.
Multimillion-dollar companies don’t guess.
Timing and luck can often explain a lot in the early days.
But when companies pass a certain threshold, and the people inside them repeat their success at multiple different places, it shows there are proven roadmaps to follow.
Not cheesy checklists or ‘guru’ charlatan soundbites.
But legitimate strategies, principles, and decision-making criteria that more often than not move the needle.
Here’s how several multimillion-dollar companies use SEO content audits to lay that foundation and consistently grow month over month, year over year.1. Start by Auditing Your Historical Performance to Uncover the Biggest Opportunities
Sales is a lagging indicator.
In other words, it’s impossible to address the bottom line – the output – until you first start fiddling with the inputs.
Gaetano DiNardi’s first task after joining Nextiva a few months ago was a competitive audit.
And it’s been the first task he’s used at every company before that, too.
In early 2024, DiNardi joined the Pipedrive team as the new SEO manager.
While leading Pipedrive’s SEO strategy and operations, he was tasked with improving everything from rankings to traffic, sales, and their overall bottom line.
“My entire job was based around inbound marketing. SEO, content marketing, inbound lead generation. The goal was simple: grow.”
The first step was figuring out what was already working, what wasn’t, and where the biggest opportunities were buried.
That takes into account:
Landing pages: Length, content, CTAs, value proposition, user flow.
Content rankings: Looking at SERP positions, competitors, links needed, and content updates required.
Keyword research: Analyzing which keywords they were targeting and finding new long-tail variations.
Ignoring vanity metrics: With SEO data analysis, he focused all of his efforts on improving the cost of acquisition and lifetime value.
Site structure: How users flow on site and where major drop-offs were occurring.
Content audit: Looking at content, cutting and deleting content that isn’t valuable, and finding what he could improve based on best practices.
Brand building campaigns: Getting mentioned in major publications like Fortune, Entrepreneur, Huffington Post, Inc., VentureBeat, and LinkedIn Business to help build Sales Hacker and his personal branding.
He started by focusing on landing pages, improving their calls-to-action and value proposition along with CRO elements to encourage conversions. Doing so increased overall conversions by 12%.
While looking at site structure, DiNardi used Google Analytics reports to analyze and optimize user flow throughout the site:
With these reports, he determined the typical path of unique visitors and how they developed brand awareness, including which posts they viewed and how many steps it took them to convert.
A traffic channel or source, for instance, gives you clues into what each visitor wants and how to help them find it.
Plus, he could then see major drop-off points and which pages were leaking visitors, giving him an easy win to eliminate those content pages or better match search intent to make them stickier.
Diving into the content audit, Gaetano focused on ensuring that each post met the best practices for content length, topic, structure, and quality.
Running skyscraper-style campaigns for content improved the length. Then, DiNardi also honed-in on quality, updating content at scale with semantic keywords and relying on automated grammar tools to reduce redundant points.
This tactic resulted in a 4-5% increase in conversions from organic search, a 20% increase in traffic, and a doubled organic keyword growth.
“Account audits are a must. You can’t know what to attack first if you don’t audit existing strategies and see what type of content you are working with.”
Uncovering these issues and opportunities is only the first step, though. The next one is to figure out when, exactly, to address each.2. Consistently Re-Prioritize Your Content Audit Opportunities to Do the Right Thing at the Right Time
Advertising used to be cost-prohibitive. So, too, was PR.
The problem isn’t having options, then. In fact, it’s the opposite. There are literally too many things you could be doing at any given time.
Content success, then, is dictated by what you choose to do and in what order.
Client-agency dynamics also played into this issue.
Typically, the most profitable strategies and tactics take a long time to develop. However, clients don’t have time. They want results ASAP.
So you’re constantly dealing with the conflict of delivering instant results to make the client happy, while at the same time building the foundation so that you’ll be able to continue delivering results long into the future.
Kevin’s approach, unsurprisingly, started with an SEO content audit at the beginning. It was in-depth, analyzing the technical set-up first, before the on-site content and optimization, then progressing to link building.
This initial audit was also used to identify potential low-hanging fruit. A simple crawl error preventing indexation, for example, could instantly deliver ROI to the client. If, that is, you knew where to look.
“Sometimes people neglect digging into that data and adjusting existing content a little bit. It’s simple, but it often has a pretty big impact. They should do this before ever starting brand new content creation.”
Jones prioritizes technical SEO, first, because “in a lot of cases it’s going to help the most.” Especially with larger websites that have changed or evolved over the years.
“It’s a slow and steady race for technical improvements. And it’s a pain in the ass to clean an entire house.”
From there, Jones moves to on-site changes, like keyword research and content opportunities.
This approach made clients happy because “they could see quicker traffic increases, but still benefit from a long-term balance for technical SEO.”
Every new website is different, so the order might be unique. But generally, Kevin would divide his time into spending around 40% on link building, 40% on content, and 20% on the technical side after the initial fix-it stage.
The mechanics are actually pretty easy. The tough part is to constantly reassess the leverage points based on where you’re already weak or strong.
For example, let’s say you want to evaluate a keyword opportunity. That decision ultimately comes down to:
Demand: The number of people searching for this term.
Competition: The number and strength of people competing for this term.
Yes, there’s more at play in reality. Yes, funnel stage and search intent and lots of other criteria are involved.
But at the end of the day, it can and should be that simple. Take “content marketing”:
Now, compare that site authority and referring domains with your own.
This example is extremely competitive. So unless your site’s been around for a while, your odds of success are slim to none. That means you either need to:
Identify a new, less competitive search query to go after.
Work to improve your off-site metrics to mirror the competition.
Either way, you probably want to deprioritize this for now. Topping out at the fifth position might as well be the 50th.
So maybe creating new content isn’t such a good idea after all. Maybe doubling down on your existing stuff will produce a better ROI over the next six months.
It’s a simple cost/benefit analysis of resource allocation at the end of the day.
Which option will provide the best, quickest return on your time and money?
It might take you anywhere from half to a full day to create a single blog post from scratch. Then, it might take another few weeks (or months) to get that page to rank.
Or, you could pick an existing page on your site that shows promise and spend the same three to six hours improving it.
Chances are, you’ll see much better results moving from the 11th position on Google to the 5th. And it’ll usually take less time, too.
SEO today is incredibly complex and nuanced. Search engines use machine learning algorithms to teach themselves new tricks.
Unfortunately, many of the get-rich-quick SEO schemes of the past work less and less with each passing day. Which means success over the long haul requires a constant reprioritization of what to do, when, and why.
Today that means one thing. Six months from now it will probably mean another.3. Reverse-Engineer Content Distribution Tactics – But Don’t Copy
First edition Pokemon cards can run into the thousands on eBay.
Seriously. Check it out:
Back in high school, David Zheng discovered this lucrative niche market. And it changed everything.
He came up with different ways to collect or barter for the most valuable first editions. Then he’d create the listing, promote it, and dutifully follow through on each order with every buyer.
Despite all the painstaking labor, Zheng started clearing five-figures as a 14-year-old kid.
The only problem?
He was supposed to attend classes during daylight hours. Which meant that packaging and mailing out products had to occur late each night.
Zheng recalls that it wasn’t just the money. Sure, it was nice. But more importantly, it was about “figuring it all out.”
Getting all of the pieces together (so to speak), in the right order, at the exact right time.
Probably the worst one you’ve seen, right? Except for one teeny, tiny, detail.
Design has little to do with it. Instead, timing does.
But the point is the same.
“Like-gating” used to be one of the best ways to get new Facebook fans. Now, that functionality no longer exists (and goes against their policies).
Some principles will always remain relevant. But when it comes to content growth, you can’t rely on blindly copying a tactic or sticking with the tried-and-true. It can only work so long online.
Instead, you have to learn, test, measure, iterate, and come up with your own unique formula.
Content marketing is a system, not a tactic.
Content tactics commonly fail. Systems adapt and evolve.
One of Zheng’s first big wins included working with chúng tôi a viral blog that hit 31 million unique visitors, while also racking up fans like Elon Musk and Sam Harris.
This experience also helped Zheng discover the formula for growing sites with content which he took and repeatedly used to grow other big sites for people like Noah Kagan, taking OkDork’s (Kagan’s personal site) organic traffic over 200% within six months.
Like most good formulas, there’s no single variable. There are lots that all work together.
For example, it could start with detailed keyword research that considers not just search volume, but also relevancy and intent. It extends to the nitty-gritty details like rich snippets that can significantly increase CTR you see from SERPs and social streams.
Then, collecting all the emails you can possibly get your hands on and building relationships with people who talk to the people you want to buy from you.
Because the stuff that you’re doing over there will affect the results you’re getting over here.
That’s why the fastest growing companies look at the entire distribution system. They’re focused on building their social following through outstanding content and funneling the results into email so they can amplify their message across multiple touchpoints. Layer in retargeting and you’ve got the beginnings of a growth machine.
These content + paid + social + email + SEO strategies that David used proved so effective for Noah that it helped inspire a decent idea, too.
You may have heard of it.
Sumo is now part of an eight-figure business.Conclusion
Content marketing success doesn’t happen in a vacuum.
And it can’t be learned by following a checklist or blindly following an influencer.
Instead, it comes with the realization that changes on one end create a rippling effect on the other.
Consistently reevaluating your top priorities with SEO content audits is critical. Not annually, but quarterly.
So the best thing you can do is get a front-row seat observing the companies already doing it. And speak with the people behind the scenes who actually perform the work.
Because you’ll quickly realize that marketing success is driven more by the sum of its parts than any one activity, tactic, or campaign.
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