How Data Science Makes Money — for BusinessesLester LeongBlockedUnblockFollowFollowingJun 17This article is mainly for two types of people: business decision makers and data scientists.
For those business decision makers, you’ll learn why you need data science in your company or discover more ways to leverage your data science team.
For data scientists, you’ll learn how your boss thinks and be able to pitch better projects.
Real talk: my boss’s boss would always walk into my presentations leading with, “Show me the money!”Secret side note: this also applies to people breaking into data science roles and need ammunition to close the deal.
Companies aren’t Maximizing Their Data into InsightsThis header is obvious for many factors.
Data science is booming.
There are plenty of companies doing data transformation (turning their old IT infrastructure into one that supports data science), data boot camps everywhere, etc.
Of course, there’s a simple reason for this: data science provides insights.
The days of a group of executives making gut instinct decision to drive the company are coming to an end.
They are being out-competed by companies that apply data driven decisions.
For example, let’s look at Ford in 2006, which took a $12.
6 billion loss [1].
After that loss, they brought in a chief data scientist to lead the transformation and did a massive three-year overhaul.
This resulted in over 2.
3 million cars sold and ended 2009 with a profit.
Underlying Business Theme: Data transformation comes from the top down Data Science Value Add: Hire data scientistsHow Data Science Adds RevenueData science can be applied to find and refine a target customer base to generate more revenue.
In sales, specifically lead management, models can analyze past customers and score leads resulting to greater sales efficiency.
Not only past in-house customer data is used but also social media interaction for scoring.
Companies that applied artificial intelligence lead scoring increased 50% more appointments and 60% reduction in call time [2].
Better leads close sales deals faster, which creates more revenue.
Underlying Business Theme: Companies seek operational improvements in salesData Science Value Add: Logistic RegressionOn the marketing side, data science improves marketing campaigns by enhancing customer profiling.
Studies have shown that correctly targeted emails lead customers to spend 38% more, and retargeted customers convert 70% of time [2].
For targeting customer emails, data science analyzes customers’ past purchases and sends customized recommendations.
Personally, I find that getting product recommendations that I actually want and need to be very valuable, and I am not alone.
86% of customers want a better experience and are 15x more likely to buy from the same business that does it [2].
Now that’s brand loyalty.
On the same note, airlines have successfully applied focus targeting through price optimization.
From their analysis, airlines found that customers are willing to pay up to 50% more as their desired departure date nears [5].
This can be applied to other businesses through analyzing their reactions to price changes from sentiment analysis.
Sentiment analysis can examine customer’s reactions to a specific event through their social media.
Underlying Business Theme: Growing customer preferences towards experience Data Science Value Add: Recommender system, Sentiment AnalysisHow Data Science Reduces Costs and RiskA study from Forrester found that 38% of businesses have analysis, but cannot effectively communicate their results into insights [2].
For example, we all have seen at least one time in our life a team member who finds some “great discovery”, but his employer simply doesn’t understand it.
This is where the data scientists steps in.
Not only do data scientists perform analysis, but they also communicate effectively into actionable business results.
Basically, no data science projects are done simply for discovery.
They are done to solve an active business problem that will increase revenue or reduce costs.
For example, in Airbnb, the marketing department thought one of their campaigns were off due to bad metrics [3].
A data scientist found the root cause to be a group in Asia using their site to browse neighborhoods.
As a result, the marketing department redirected that group to a travel site, which clarified their marketing metrics and saved resources instead of launching an inefficient marketing initiative.
In my own personal experience in financial services, we have applied data science concepts to reduce customer turnover and fraud risk.
Using time series analysis, we predict when customers are likely to get into trouble and offer assistance to prevent breaches in contract.
As for fraud prevention, we analyze client data to detect anomalies that might be fraudulent, which leads to a potential savings of over $20 million a year.
Underlying Business Theme: Current data science technology allows for more precise and accurate insights Data Science Value Add: Auto Encoder, Time SeriesHow Data Science Improves TalentInnovation can come from borrowing ideas from different fields [4].
One method is to improve hiring practices, like hiring more women.
Let’s take a lesson from Airbnb’s playbook.
For example, when Airbnb wanted to hire more women, they discovered that they had 30% female candidates per job opening [3].
There was no excuse not to find qualified candidates with that large amount of applicants.
As a response, they optimized their hiring practices specifically for getting more women employees.
To speed up the process, they used a mix of machine learning and deep learning techniques to filter down the best candidates.
Underlying Business Theme: Corporate trend towards diversity in the workplace Data Science Value Add: Natural Language Processing (NLP)ConclusionCompanies now need to apply data science as a part of their business and culture.
Not doing so leaves too much money on the table.
The company’s data without data science is like that piggy bank.
The data alone does not provide actionable insight.
Data science unlocks its value.
Break the piggy bank and apply data science.
Invest in data science to make your company have better data, better decisions, and better profits.
Feel free to comment below or reach out on LinkedIn.
I read every comment and not my NLP systems.
For the next articles, I’ll start posting some coding walkthoroughs.
Been getting a lot of requests, and I heard all of you!Disclaimer: all things stated in this article are of my own opinion and not of my employers.
[1] E.
McNulty, 5 Ways a Data Scientists Can Add Value To Your Business (2014), https://dataconomy.
com/2014/11/5-ways-a-data-scientist-can-add-value-to-your-business/[2] T.
Capone, How Data Science Can Help Your Enterprise Generate More Revenue (2018), https://conceptainc.
com/blog/how-data-science-can-help-your-enterprise-generate-more-revenue/[3] N.
Patel, How Airbnb Uses Data Science to Improve Their Product and Marketing (2019), https://neilpatel.
com/blog/how-airbnb-uses-data-science/[4] B.
Harpham, How Data Science is Changing The Energy Industry (2016), https://www.
cio.
com/article/3052934/how-data-science-is-changing-the-energy-industry.
html[5] Altexsoft, 7 Ways Airlines Use Artificial Intelligence and Data Science to Improve Operations (2018), https://www.
altexsoft.
com/blog/datascience/7-ways-how-airlines-use-artificial-intelligence-and-data-science-to-improve-their-operations/.. More details