This article will be useful for business analysts, marketing specialists, marketing analysts, data enthusiasts, and business owners.
If you’re interested in analytics, you’ll definitely find something useful below. There are multiple categories so pick which one interests you most, or – if you’re feeling adventurous – go through all of it.
What you’ll find below:
- Top books for analysts
- Top case studies for analysts from 2018
- Top questions for analysts at job interviews
- Top tools & apps for analysts
- Top blogs for analysts
- Top analytics companies
- Top trends for analysts in 2019
Top books for analysts
Are books the best means of self-education for you? Here’s a perfect list for your evening reading ritual.
Superforecasting: The Art and Science of Prediction by Philip Tetlock and Dan Gardner
This book is so easy to read. And so easy to put into practice. The most interesting part is about predictions based on uncertain data. This is an exciting book for any analyst to read over the weekend.
Analytics: How to Win with Intelligence by John Thompson & Shawn Rogers
This book talks about a few interesting cases from 30 years of the author’s practice. Learn how to turn big data and other sources of information into valuable knowledge, creating a competitive advantage to propel your business toward market leadership.
Business Case Analysis with R by Robert D. Brown III
No one can ignore programming skills nowadays! R is one of the most widely used tools for reproducible quantitative analysis. This book teaches you, in a very conversational style, how to use the statistical programming language R for business needs.
The R language, traditionally used for statistical analysis, also provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis.
The Failure of Risk Management: Why It’s Broken and How to Fix It by Douglas Hubbard
The risk management industry is evolving all the time. This book is good for both professionals and beginners as it has real-life examples and covers the theoretical basics. It’s applicable for any level of management.
Measuring and Management Information Risk: A FAIR Approach by Jack Jones and Jack Freund
Learn all about the FAIR model and quantitative measurement approaches, and get insights into how a risk management program can provide value.
For some marketers, it’s easier to become superman than a big data specialist. If you’re such a marketer, start reading this book. It’s designed to give marketing professionals a focused introduction to the trendiest technologies and how they’re being applied in marketing. Jim Sterne walks you through the need-to-know aspects of artificial intelligence, including natural language processing, speech recognition, and machine learning.
Principles of Marketing Engineering and Analytics by Gary Lilien, Arvind Rangaswamy, and Arnaud De Bruyn
Marketing isn’t a humanitarian discipline anymore! This book focuses on Marketing Engineering, which the authors define as a systematic approach to harnessing data and knowledge to drive effective marketing decision-making and implementation through a technology-enabled and model-supported interactive decision process.
This book provides a new view on modern PR rules for a variety of PR tools, with instructions on how to implement them. It offers a great analysis of different channels from successful practitioners with lots of experience.
Enchantment: The Art of Changing Hearts, Minds, and Actions by Guy Kawasaki
Do you know what the three pillars of enchantment are? This book will tell you. Also, you’ll find out how to apply them in your everyday life and in the work environment.
In this delightfully readable book, practically every page has an insight that will change the way you think about the new era of social media. The collective mind isn’t an empty concept anymore.
Top case studies for analysts from 2018
Let’s see which case studies from 2018 set the bar for top performance and where we can draw inspiration from.
Sephora’s investment in AR and data analytics
Sephora is a multinational chain of personal care and beauty stores with an almost 50-year history. And it’s quite modern. Their latest campaign is an app that uses augmented reality and artificial intelligence to let users try different makeup products they can find online and in the store.
How cool is that? During makeup try-ons, Sephora’s app gives advice and interesting tips, collects feedback, and gently leads customers to the checkout. The company’s analytics are enriched with lots of funnel-based e-commerce data and first-class user experience information.
What’s been the result? Customers have tried on 200 million shades during more than 8.5 million visits to the Sephora Virtual Artist. Nailed it!
Great predictions by American Express
All analytical efforts at American Express have been concentrated on loyalty. Is 115 variables enough to estimate the churn rate?
Now, American Express predicts their four-month churn rate at 24%. They have plenty of work to do with those customers who might churn!
Duetto helps you find the hotel of your dreams
Analytics has made it easier for companies to personalize hotel offerings. Duetto uses data on the prices of services and goods that users buy online (based on online searches) to determine the prices of apartments or hotel rooms to display.
Netflix is even more interesting because of this…
The team at Netflix is quite impressive. In their fight against sleep, they’ve taken analytics to a new level. Now they’re processing cosmic amounts of data on international viewing habits to offer the best programs for large and varied audiences.
Next Big Sound tells you who’ll be on TV tomorrow
Who will wake up as a famous star? This is the question Next Big Sound is answering with analytics based on Wikipedia page views, Facebook Likes, YouTube views, and Twitter mentions. This service is more reliable than those music analysts on the talk shows.
Procter & Gamble has created a data-based “one ring” to rule them all
Procter & Gamble gathers petabytes of structured and unstructured data across research and development, supply chain, customer-facing operations, and customer interactions both online and offline. Their main task in 2018 was to combine all of this data.
Raiffeisen finds fraud in the CPA network
To prove a hypothesis about affiliates rewriting traffic source data to their benefit, Raiffeisen marketing specialists decided to start collecting raw user behavior data. Based on this information, Raiffeisen stopped cooperation with webmasters acting in bad faith and optimized their marketing budget. Saving money is a talent. Be talented like Raiffeisen.
Red Roof Inn as a harbinger of hospitality
An estimated 2–3% of flights are cancelled daily at O’Hare International Airport. That means 500 planes don’t take off, leaving 90,000 passengers stranded. Red Roof Inn uses big data to identify demand and uses search advertising, mobile communications, and other methods to drive digital bookings with personalized messages like “Stranded at O’Hare? Check out Red Roof Inn.”
The results have been great. Red Roof Inn has seen 10% growth year over year. That’s how profitable it is to be at the right place at the right time.
Language-based analysis by Walmart
Walmart implemented three great ideas at once: text analysis, machine learning, and synonym mining. Walmart says that adding semantic search has led to an increase of 10–15% in the order completion rate for online shoppers. In Walmart terms, that’s billions of dollars.
Top questions for analysts at job interviews
You may ask these questions eventually. Or you may have to prepare for them if you want to be an analyst. Some of them are too simple or too specific, but you must be ready for them anyways.
- Why did you go into data analysis?
- How would you explain your job and its importance to your grandmother?
- How do you deal with difficult stakeholders?
- Talk about a time when you couldn’t meet a deadline.
- Tell me about your typical approach to a project.
- What do you see as the key strengths of an analyst?
- Can you name tools that are helpful for business analysis?
- What is meant by benchmarking?
- How would you differentiate a risk and an issue?
- What diagrams should a BA know?
Top tools & apps for analysts
Modern analysts are flooded with tools and technologies to adopt in their work. And there’s no other way to choose what’s best for you than to try and try again. Here’s a list of tools for analysts — and for you — to try in 2019.
- Mixpanel — Web and mobile analytics
- AdWords Performance Grader — 60-second PPC audit? Nailed it.
- Formisimo — Form analytics platform
- BuzzSumo — Social and content analysis
- Crowdbooster — SMM for your business
- Moz Link Explorer — Advanced link profile diagnostics
- Trello — Manage your tasks
- OWOX BI — Combine all business data from any source
- Canva — Create a New Year’s postcard
Top blogs for analysts
A good analyst is a good reader. And even a writer or blogger! Follow these blogs to stay on the cutting edge of marketing analytics and learn interesting tips and tricks for analysts.
- Occam’s Razor by Avinash Kaushik
- Simo Ahava Blog
- Harvard Business Review — Analytics
- Moz Blog
- Content Marketing Institute
- HubSpot Academy
- OWOX BI Blog
Top analytics companies
This list based on Clutch rankings. Clutch is a platform with in-depth client reviews and data-driven content that showcases vetted market leaders. These market leaders differ from each other not only in the services they provide but also in their approaches and philosophy. But all of them are obsessed with analytics and delivering value to clients.
- CBIG Consulting
- Anthem Marketing Solutions
- LatentView Analytics
- Statistics Solutions
- Rudder Analytics
- Beyond the Arc
- Treselle Systems
- Cartesian Consulting
Top trends for analysts in 2019
These are mostly Gartner’s predictions. Maybe they’re somewhat vague, but they catch the biggest undercurrents that are making analytics the right hand of modern business and society.
Data storytelling culture
The data structure inside a company describes its level of development and hides a lot of insights. Data storytelling culture refers to how written communication, stories, and data flows inside a company shape its internal structure and development.
Data curation is the process of capturing, cleaning, defining, and aligning disparate data to bridge the gap between data and its real-world applications. We’ve created a virtual world and enriched it with data. Now we need to make data accessible and easy to use for humans, machines, and systems.
NGOs and nonprofits create data commonwealths
NGOs and nonprofit organizations are becoming players in the data market, democratizing access to data and creating a data commonwealth to bring value to society. And these organizations are often the most reliable sources of data because they gather data from special channels like research groups that have unique technical insights and do their own investigations.
New codes of data ethics
Citizen data scientists are the most interesting contributors to the future of analytics. They care about the practical implementation of new discoveries. The appearance of these specialists will seriously impact politics and social relations.
The growing importance of the CDO & CAO
At last, C-level analysts are getting the power and influence they deserve! If you want to be successful with data, choose your Chief Data Officer & Chief Analytics Officer well.
Virtual, augmented, and mixed realities are new ways to explore the digital world. Our devices have become nothing more than keys to a brand-new world of possibilities.
This trend describes a new wave of analytics that uses machine learning to set and test hypotheses and build automated reports into enterprise applications. A good example of a company that’s developing in this way is OWOX BI.
This trend is about creating digital twins of anything that exists in real life, whether a process or entity. We have a lot of work to do on this front because the virtual world will never be overpopulated.
Analytics and data is a vast space, with loads of segments, uses, business cases. Choose what interests you more and explore it deeply. Then do it again with an adjacent niche.
PS. When I read Superforecasting: The Art and Science of Prediction there was a tool mentioned which was meant for calibrating of your judgments. What’s judgment calibration? It’s how good you are at predicting uncertain events or facts. It’s not how right you are, but rather how good at assessing the probabilities. For example, if you say that you’re 60% sure of something, you’re actually right about 60% of the time. This is crucial for good judgment and for being neither too optimistic, nor too pessimistic.
I have found a tool online which measures and calibrates your judgments. Take a test and see how good you are at judging your own predictions: http://calibratedprobabilityassessment.org/
And read the book as well, it’s great!