Cloud Commerce Consulting

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Stop Budgeting For Sales and Marketing

Bootstrapping At Scale

One famous Silicon Valley axiom is that nothing is a better teacher than being cash strapped. And many venture-backed firms who have closed huge rounds have gone on to make massively costly mistakes. That is why we promote strategies that achieve scale and triple digit annual growth with self-funding programs that require very little investment capital.

Sales & Marketing Should Power Themselves

Several of our startup and growth-stage firms come to us after their home-grown sales and marketing strategies have not driven projects returns. Often they plowed large budgets into activities that were for “long-term” goals or with long payback cycles. Simply put, don’t do these. Make it clear that sales and marketing are there to feed the organization, not the other way around.

Don’t Spend Money if The Results Cannot Be Proven

A professor once told me that “strategic” is a management uses when they want to do something that they know will lose money. Internet marketing and direct selling have the advantage of offering lots of data-driven activities. Insist on understanding the marketing pipeline and what the metrics are so you can trace every dollar from initial lead generation activity to receipt of bookings.

Short ROIs are the only ROIs

Digital marketing spend should be able to result in profitable dollars in within 90 days or don’t do those activities. Prioritize scalable, low-cost selling over high cost selling at all turns. Also prioritize scalable solutions wherever possible. Don’t do expensive, outside enterprise selling until you have concluded there really is no other way to grow. one of our clients achieved their first ever profits by cutting outside selling investments and focusing on new digital marketing and inside selling tactics that drove higher volumes of easier to collect subscription sales. They built all this while becoming profitable with relatively little up front incremental investment.

Stay Home First

Human nature means doing what you like and what has succeeded for you in the past. This often leads leaders to emphasize higher cost, slower sales models than  they need to. If you can make money by direct, automated selling through digital marketing then optimize around that and scale as large as you can before looking at other selling models. Look next to inside sales models before looking to outside models. Outside selling is a critical practice for many firms but is typically the slowest to grow with the longest sales cycles and the hardest to scale so do not assume it is your only option.

Beware Outsourcing

There is a time and place where outsourcing can help with scale but never when you are early stage or unprofitable. You must be able to generate leads and close them yourself before you can outsource that to another company. Similarly, indirect selling such as though partners or channels has its place but should be a last resort. Nobody will ever care about your sales growth as much as you do.

Slice data, then slice again

Everyone wants to be data driven, but doing it successfully means slicing data and looking at cohorts while eschewing averages. Averages hide treasure. Encourage large amounts of short, inexpensive tests. It could be that one lead traffic source with one landing page with one call to action with one inside sales strategy and script is massively more profitable than the others. It is not true that you can treat marketing and sales as distinct activities. Leads generated from different lead sources rarely will respond the same to your sales strategy. Assume they will not. Even small changes in copy or call to action can convert different leads or set different expectations that cascade to very different sales experiences. Drill into that and plow your money into that cohort to scale it. This has allowed us to make many, many clients massively profitable on strategies they thought were disproven.

Michael Zammuto argues that AI Bias Can Do As Much Damage As Data Breaches


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Bias is the new “Breach” – Managing Bias Risk in an Automated World

In The Next Decade, AI Bias Will Do As Much Damage As Data Breaches

Data breaches are a terrible risk to enterprises. We run off data and a breach mean a failure in the commitment to safeguard data. It leads to hug costs to an enterprise; civil and sometimes criminal liability can follow. Allowing bias to creep into AI algorithms can have a similar destructive impact on the firm and, as I wrote this week on CIO.com, I believe that the next 10 years will prove that out.

Reliable Data

An AI system is only as good as the data we provide it. If we’re providing it with biased data sets, it’s going to produce biased outcomes. Software engineers and project managers have to be conscious of this possibility and they have to work to prevent it. If the system starts with a clean data set, we can be confident that it will provide valuable assistance to a business organization.

Introducing Systemic Diversity

It’s probably not enough just to avoid biased data sets though. AI is a technology that’s designed to grow and evolve – we must work hard to ensure it can recognize the diversity of our society and organizations. Recently there have been stories in the news of facial recognition systems that have trouble with anyone that isn’t white and male. If we’re going to avoid these issues, AI systems must be introduced to as much diversity as possible.

Training and Testing

As humans, we aren’t born with personal biases and prejudice. These are things we develop over time as we’re influenced by our family, friends, and society. The same thing can happen in our AI systems if we’re not careful, no matter how much care we take to avoid it in development.

If we’re going to make sure that AI remains free from bias in our business systems, we have to be constantly re-evaluating and upgrading. Programmers must be trained to spot it and the average end user must have the tools to help correct it as well.

There is obviously much, much more to say on the topic. To read more you can start here.

About the Author

Michael Zammuto is CEO and chief consultant for Cloud Commerce Consulting

Michael Zammuto on Automation and Jobs


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CIO.com: Getting Business Buy In When AI Destroys Jobs

Automation Will Destroy  Jobs – How Do You Get Organizational Buy In For That?

Michael Zammuto's Column On CIO Magazine's site - Practical AI, Data and Analytics Strategies

Michael Zammuto’s Column On CIO Magazine’s site – Practical AI, Data and Analytics Strategies

In his latest installment on his CIO.com column, Cloud Commerce Consulting CEO, Michael Zammuto talks openly about automation. Enterprise IT initiatives need business partners to succeed. But AI focuses on automation and that means job destruction along with productivity gains.

Many AI initiatives offer a new challenge. We have the ability to automate not just manufacturing, field, service and support jobs but, increasingly white collar, leadership and technology roles. He argues that this means AI will challenge the empires and possibly the careers of the very people you need to drive the initiative. In his article, he talks about innovation, buy-in and the reality of white collar automation.

 

 

 

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Michael Zammuto's Column On CIO Magazine's site - Practical AI, Data and Analytics Strategies


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CCC on CIO.com – AI Can Fix Your Data For You

AI is Different Because Scales With Data

Cloud Commerce Data

Cloud Commerce & AI Can Help Make Projects Scale

Cloud Commerce Consulting CEO, Michael Zammuto wrote recently on his CIO.com column about the impact of data challenges on IT initiatives. Mike argues that many promising IT initiatives stall because they depend upon data being cleaned, enriched or combined as a precursor to success. BI and analytics projects are particularly dependent upon good data. Even with the best traditional tools and techniques, the process of preparing data for these projects does not scale well, often negatively.

This means trouble for IT chiefs and business sponsors alike. Mike argues that because machine learning algorithms can learn to categorize and clean data better as you as it processes more data, this means that AI is the only approach that scales data projects well.

 

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Artificial Intelligence Strategies for Small Business

How Small Businesses Can Use AI to Outrun The Competition

Cloud Commerce CEO Michael Zammuto recently published an article on artificial intelligence and related technologies. He argues that “AI” is often used an umbrella term for a shift to a digital-first strategy of automation and learning. He provides an overview of Machine Learning, Smart Robots, Virtual Assistants, Speech Recognition, Natural Language Generation and Decision Management as key technologies for most businesses.

 

Michael Zammuto's Business.com article on artificial intelligence

Michael Zammuto’s article on artificial intelligence strategies for small business

Zammuto argues that unlike other major digital technologies, these collectively represent a disruptive force that can move too quickly for companies to safely adopt a fast-follower strategy. he points to Amazon using their data and technology advantages to simultaneously compete in diverse spaces against grocery stores, robotics companies and cloud providers as an example that these technologies can allow disruptive competition to come from unexpected outsiders.

He proscribes a strategy for small businesses to focus on using current analytics and data initiatives to gain operational advantage and then reinvesting that into commercial products like virtual assistants that can easily be adapted to a company. After that, small companies can further develop internal skills and expert connections to make additional, highly targeted and strategic investments.

Zammuto advises focusing on using virtual assistants followed by investments in NLG analytics platform to realize quick cost and performance benefits. with better data capabilities he suggests focusing on a single, potentially transformative, part of the business for another investment. Be the best at that thing, he argues, and gain a focused, impactful advantage in one area. This can be cost, service, product, quality, logistics or other areas but make sure it has the potential to change your position within your industry. This he concludes will start you on a virtual cycle of innovation and differentiated advantage that can make any small business a leader.

The full article is available on Business.com.

 

 


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AI Strategy IS Business Strategy

A New Innovation Model: Amazon Evolved from Books to Cloud and Groceries & Meal Delivery

Data, AI, Automation, Quantum Computing and the Post-PC Revolution

IDC projects that total worldwide data will be 163ZB (that is a trillion gigabytes) in five years. The power to transform our world is locked up, unused and unstructured, in this data. Fully a third of business leaders say they cannot access their own data in meaningful ways, let alone discover all new insights from it.

Michael Zammuto Technology Ecoystem Diagram

Cloud Commerce Consulting Strategic Technology Ecoystem

A strategic cluster of technologies will take a fast-growing flame of human knowledge and accelerate it into a chain reaction, immeasurably larger and hotter than anything imagined today.

Innovation in cloud, data and analytics have lit a fuse. EDM and machine learning added fuel and commercial AI and Quantum Computing will launch self-fueling chain reaction.

Cloud accelerated data, data accelerated analytics, analytics accelerated automation, EDM accelerated analytics, AI accelerates automation. Quantum computing will supercharge the whole ecosystem. 

AI Growth Accelerating Past 300% a Year

Forrester says businesses investment in machine learning and artificial intelligence (AI) will increase 300% in 2017 than in 2016. Current generations of Machine Learning technologies allow us to analyze data at scale and will ’drive faster business decisions in marketing, e-commerce, product management, and other areas of the business by helping close the gap from insights to action.’ AI will be used to automate discovery, experimentation and even coding and further AI. It is a self-fueling technology with no practical limit in scale.

Rose’s Law of Quantum Computing is Moore’s Law on Steroids

Rose’s famed predictions for Quantum Computing tell us that we are about to break Moore’s Law forever. For all our technology improvements, we compute much like we did decades ago. We don’t know when we will get commercial devices that use quantum states in place of binary values. But we know when we do it will change everything. Quantum devices will allow AI to solve problems and innovate, manage data and develop insights at orders of magnitude greater than imagined today.

The End of Tools

Computers, data, cloud services, analytics tools and so on are tools. Better, more powerful, easier to use tools. AI fuels automation and, when hyper-charged with quantum computing power, takes the tools out of our hands. The chain reaction of all this means innovation at speed and scale that will require new terms for measurement.

The Amazon Innovation Model

This means that humans will primarily contribute principles, strategies and vision to the next revolution. Those who don’t focus on building strategy and capabilities now will be left behind. Companies of all sizes and in every industry need to develop a strategic road map. Innovation will come to every industry and from unexpected directions. The model that took Amazon from books to challenge cloud computing and retail food and meal services is the future of innovation. Their strategic competitive driver is data and computing power. They didn’t expand or pivot into new businesses, these businesses were exposed to disruption by anyone who could innovate using this new model.

Contact us today. CCC helps business and technical leaders to develop these strategies and capabilities to ensure more than their survival.


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Michael Zammuto in the news

I have been dividing time lately supporting Completed.com and developing a new selling program for a client in the digital marketing space. That client has a valuable offering and has found an eager market for it but needs a scalable sales architecture to reach their potential.

At Completed.com we have been heads down on a new development cycle. We had a investor commit another $250k and have put most of that towards enhancements to our UX. The team is doing an outstanding job and we have brought some very gifted new people to the team so that project is going very well. I have been doing as much media as possible during this time. This includes a podcast interview with Neil Hughes and an accompanying article he did on The Next Web. We also have gotten great coverage from Cheddar TV, Fast Company, TechCrunch and others so I am very happy with this. It is amazing how full and fulfilling the days can be and the time is just flying by. I am really looking forward to the next release in late June.