I once worked with a retailer who was convinced their TV ads drove foot traffic. Regression analysis proved the ads did nothing, but the weather (sunny weekends) drove 90% of their sales. They had been wasting $2M a year on ads.
When stuck between two good options, ask: “Which variable is most expensive to improve?” Usually, the answer is to stop optimizing the thing that’s already "good enough." 3. The "Spaghetti on the Wall" Technique (Regression Analysis) You think you know what drives your business. “When it rains, our umbrella sales go up.” Duh. analytical techniques in business
Here’s the uncomfortable truth: In a world moving at algorithmic speed, a gut feeling is no longer a strategy. It’s a gamble. I once worked with a retailer who was
You might just save your business from its own best intentions. Struggling to make sense of your messy data? Reply to this post with your biggest analytical headache—I’ll help you pick the right technique to solve it. When stuck between two good options, ask: “Which
Stop looking at aggregated totals. Segment your data by time. Are your new customers behaving like your old customers? If not, fix the gap, not the product. 2. The "Least Worst Decision" Technique (Optimization & Trade-offs) Life is full of trade-offs. Do you lower prices to gain market share, or raise prices to boost margins? Do you speed up delivery to make customers happy, or slow it down to save on shipping costs?
But what about the weird stuff? “Does the day of the week affect our SaaS trial conversion rate?” “Does the color of our ‘Buy Now’ button actually matter?”
You aren't Amazon. Don't chase 100% perfection. Find the 80% solution that costs 20% of the effort.