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(This article was first published on <strong><a href="https://www.mango-solutions.com/blog/earl-london-interviews-jasmine-pengelly"> RBlog – Mango Solutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p><span>With EARL just next week, we have just one more speaker interview to share!</span></p>
<p><span>In today’s interview, Ruth Thomson, Practice Lead for Strategic Advice spoke to Jasmine Pengelly, whose career includes teaching Data Analysis and Data Science at General Assembly and permanent positions as a Data Analyst at Stack Overflow and DAZN.</span></p>
<p><span><br>
</span><span>Jasmine will be presenting a lightning talk “Putting the R in Bar” where she will show </span><span>how businesses can make data-driven decisions using the example of a Cocktail Bar.</span></p>
<p><span><br>
</span><strong><i>Thanks Jasmine for taking the time for this interview. Where did the idea for this project come from?</i></strong></p>
<p><span>The idea came to me organically. My fiance owns a cocktail bar and it was clear to me how they could improve their business using advanced analytics even with limited technical expertise.</span></p>
<p><span>I started asking, what insight would be valuable to the decision makers in that business?</span></p>
<p><strong><i>So where did you start?</i></strong></p>
<p><i><span><br>
</span></i><span>I identified that I had two datasets to work with. Customer reviews which were spread over four separate websites and cocktail sales information.</span></p>
<p><span>The cocktail sales information led me to consider the choices on the menu. The decision of which cocktails to put on the menu had previously successfully been made using intuition, but there had been no data driven-decisions up until that point.</span></p>
<p><span>My approach was to use exploratory data analysis to build the best menu. I also started experimenting with regression models and I’ll be touching on my findings in this area in my talk.</span></p>
<p><span>For the other areas, I used text mining and natural language processing and I’m looking forward to sharing more detail about these two use cases at EARL soon.</span></p>
<p><strong><i>What other businesses do you think would benefit from these examples?</i></strong></p>
<p><span>The beauty of predictive analytics is that any business that provides a service to </span><span>customers would benefit from using insight to make better decisions. It’s even more important for service-based businesses who also benefit from word of mouth marketing and referrals.</span></p>
<p><span>For many small and medium-sized business, analytics could be seen as difficult to use and complex. However, it doesn’t need to be.</span></p>
<p>We hope you’ve enjoyed our series of speaker interviews leading up to EARL London, we can’t wait to hear the talks in full.</p>
<p>There’s still time to<a rel="nofollow" href="https://earlconf.com/2018/london/" target="_blank"> get tickets.</a></p>
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