Feb
Data Science Team: Build or Rent?
Eric Layland 0 comments artificial intelligence, Burning Questions
Building an Efficient & Effective Data Science Team
There are numerous reasons why a company may decide to develop a data science team in their organization. The skills an in-house team brings can enable organizations to turn raw data into strategic assets. Their skills lead to better use of data assets including understanding customer behavior, error detection, automation of repetitive tasks, and overall more sophisticated decision support. A data-driven organization can benefit and gain a competitive edge.
However, building an effective and efficient data science team is not as simple as adding new hires. Before we can discuss whether to rent or build a team of experts, it’s essential to understand the roles typically needed to fully staff a data science team.
The included salary estimates do not include benefits. The figures are an average of the latest available data from Salary.com, PayScale and ZipRecruiter and reflect US labor markets.
Feb
Marketing AI Curious? Here’s 7 Key Questions to Ask
jerry9789 0 comments artificial intelligence, Burning Questions
Artificial Intelligence(AI) has recently been integrated into marketing and is still in its early stages. It makes automated decisions based on available data and audience observations or economic trends that impact marketing. By doing so, it enables marketers to gain more insight and understanding of their target audiences.
However, a business must comprehend how AI Marketing works and its effects before adopting it. Here are seven questions every company interested in AI Marketing should ask themselves.
Feb
“Data Scientist in Residence”, “Chief Data Officer”, “Big data engineer”…the data science buzzword du jour is “Data Scientist.” These data scientists are part data analyst, part statistician and part software developer. With data quickly becoming a top strategic business priority for many companies, the need for data scientists will only increase – especially as we move toward an ever more data-driven world.
If data represents a strategic asset for your company, then you should be wondering if a data science team is needed and is it better to buy or rent the talent? Data analysis can be done by anyone with analytical skills, right? Well, the functions of a data scientist on a data science team are broader than initially meets the eye….and they typically need to work closely with data analysts and subject matter experts.
Data Scientists are in demand, and the salaries for US-based professionals can easily reach six-figure levels (about $120K + benefits according to Indeed). The number of data science jobs is expected to grow by 24% over the next five years. But do you really need a team of data scientists?
Jan
At The Core of Marketing Decision Making: Advanced Analytics
jerry9789 0 comments artificial intelligence, Burning Questions
Advanced Analytics is an encompassing term that is used to categorize techniques and technologies that seek to understand what happened in detail or to predict what may happen with an unmatched degree of precision. We use the term to encompass services that include Data Science, Artificial Intelligence, or AI and related technologies. The field of AI-powered Advanced Analytics draws on various aspects of neuroscience, statistics, mathematics, and computer science. But perhaps more critically, it is heavily influenced by the disciplines of philosophy and psychology to understand human motivations.
Jan
Curious About AI in Marketing? 7 Critical Questions
jerry9789 0 comments artificial intelligence, Burning Questions
Artificial Intelligence(AI) has recently been integrated into marketing and is still in its early stages. It makes automated decisions based on available data and audience observations or economic trends that impact marketing. By doing so, it enables marketers to gain more insight and understanding of their target audiences.
However, a business must comprehend how AI Marketing works and its effects before adopting it. Here are seven questions every company interested in AI Marketing should ask themselves.
Jan
Leadership in 2023 Begins with Advanced Analytics
jerry9789 0 comments artificial intelligence, Burning Questions
Since the advent of Big Data Analytics over a decade ago, the challenge has been to gather the data so that you can see the data and display it in such a way as to allow it to be useful in the day-to-day processes of a business. Dashboards are very popular for this exercise— and rightly so. However, your dashboards are a crutch used to identify things from the past and correct them. They help you learn the 6… 8… or 10 things that your team needs to work on in a given amount of time. But they give you false KPIs.
Dec
Latent Effects Modeling with AI & Machine Learning
jerry9789 0 comments artificial intelligence, Burning Questions
We’ve been posting opinions and comments that urge marketers to “get over” artificial intelligence (AI). To dive into AI’s veritable treasure house of research tools and insights, instead of circling it warily, for fear of banging into a “disruption” moment.
Marketers: use advanced analysis techniques for deeper insights
So, I hereby plant the flag of AI for the regular guy (or gal, of course) — well, at least for the professional who wants to use precise and accurate data to propel insights that simply wouldn’t be perceptible with traditional approaches to analysis.
Dec
An Artificial Intelligence Glossary of Common Terms
jerry9789 0 comments artificial intelligence, Burning Questions
Developing a basic understanding of use-cases, trends, and applications for Artificial Intelligence (AI) is helpful to understand the context in which AI is deployed. Keep in mind “AI” is sometimes considered too broad to be a distinct “field.” Rather it is a technology “concepts” with clarifying needed to properly frame discussions on the topic. Therefore we’ve assembled broad definitions to help readers develop a basic vocabulary for communicating about the subject. Think of this glossary as similar to the old Berlitz travel guides of “essential terms” for a given language.
Advanced Analytics
AI introduces a whole new vocabulary to marketing.
A part of data science that uses high-level methods and tools to focus on projecting future trends, events, and behaviors. This gives organizations the ability to perform advanced statistical models such as ‘what-if’ calculations, as well as future-proof various aspects of their operations. The term is an umbrella for several subfields of analytics that work together in their predictive capabilities.
Nov
Applying AI: Healthcare Enrollment Optimization
Aleksey 0 comments artificial intelligence, Burning Questions
Proper application of AI techniques can yield clarity and precision of insights.
Here’s a case where AI rolled into the ongoing rollout of the Affordable Care Act (ACA). To avoid getting lost in the weeds, let’s just recall that there were big-money battles involving healthcare providers, the Federal government, and the confused, newly ACA-insured and wanted-to-be insured.
Nov
Truth to Marketers: AI is a tool, not THE solution
Aleksey 0 comments artificial intelligence, Burning Questions
Capable professionals know AI is a tool to aid solving problems. Alone it is not a solution.
Our previous post urged fellow marketers to “get over” the artificial intelligence (AI) hype. To stop thinking it’s all about “disruptive,” high-tech tools on the bleeding edges of the frontier. The VR goggles. The eye-tracking studies. The neuroscience applications.
Yes, there are plenty of far edges out there, and we’re often leading them for our clients from the edge into the everyday. But look, today, AI is disruptive only if you didn’t see it coming years ago. It’s now hanging out in the research tool shed with longtime favorites like (examples?)
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