Techniques For Understanding Consumer Buying Cycles

🧠 10 questions everyone should be able to answer about their products/services... Most brands focus on what people are buying. The better ones figure out who is buying. But the best? They understand why people buy. Here are 10 of the most powerful questions I use to uncover real buying behavior. Each one is designed to go deeper than the data: 1. What job is this product really doing for you? Uncovers the functional or emotional "hire" behind the purchase. 2. When did you last choose this product—and why then? Surfaces situational triggers and decision-making context. 3. What made you hesitate before buying? Reveals friction, confusion, or barriers to purchase. 4. If this product disappeared, what would you replace it with and why? Identifies the true competitive set and how buyers perceive the category. 5. How does this product make you feel when you eat or drink it? Digs into emotional motivators like comfort, indulgence, or trust. 6. What does buying this say about who you are or want to be? Explores personal identity and self-expression. 7. What are you hoping this product will help you achieve or avoid? Taps into transformational or aspirational goals. 8. Who else influences your decision to buy this? Highlights social proof, family dynamics, or cultural pressure. 9. What would make you stop buying it? Uncovers potential weaknesses or emerging threats. 10. How would you describe this product to a friend? Exposes perception gaps, brand storytelling effectiveness, and real language. ------------ The answer to these questions tells you why people buy. If you’re not asking them, you’re probably guessing. And guessing is expensive.

There are several key ways to boost sales on Amazon. One of the most impactful: Target your customers when they are most likely to buy again. To do this, you need to understand your customer’s repeat purchase behavior. Here’s how we do this for our clients: At Cartograph we built an analytics dashboard to help our clients better understand the repeat purchase behavior of their customers. The data was being produced by the customer and ingested by the brands, but it wasn’t being leveraged to its greatest potential. So Cartograph build tools to analyze, visualize, and act on this data. What we discovered was different from what we expected. We segmented repeat purchases into 4 categories: 1. How many people repurchase within 0-15 days? 2. How many people repurchase within 16-30 days? 3. How many people repurchase within 31-60 days? 4. How many people repurchase within 3 months? For some product categories, we created additional cohorts for as far as 6 months beyond the initial date of purchase. When repurchases were grouped into cohorts and spread across an x-axis, a strange curve emerged in the graph. It was a bimodal distribution: The first peak occurred within two weeks of the initial purchase, then a trough, and then a second peak between month 1 and month 2. When we began to connect other brands to the Repurchasing Dashboard, we saw the exact same results with varying intensity — Two peaks, one trough. After weeks of research, we were able to piece together the cause of this behavior. Take, for example, a tube of toothpaste. A single tube will last about 3 months before it has to be replaced. Therefore, you would expect to see a single slope that grows exponentially as it approaches the 90-day mark. But, there are a shocking number of repeat purchases between days 0 and 15. As it turns out, the most likely (and most common) explanation for this consumer behavior is: - Stocking up with a larger supply of the product - Deciding to order more of that same item (or a slight variant of that item) for yourself or for friends/family. - Clicking “Buy Now” twice in a row (instead of adding several items to a single cart) That’s why, for every single product, we saw two large repurchasing spikes: One at the beginning and one towards the end. That’s what makes this so interesting — From our analysis, many of those curves have bimodal distributions of varying shape and intensity. In fact, we found that the most common repurchasing behavior came 30-45 days after that first transaction. This allows us to help our clients by tailoring our look back windows with DSP to target customers when they are most likely to buy again. As a marketer, the more familiar you are with that curve, the better equipped you’ll be to answer those three vital questions: “What products should I be promoting?” “When should I be promoting them?” “Who should I be promoting them to?”

I remember years ago working with a coffee brand, and we discovered some fascinating insights from analyzing customer buying behavior. We had two types of purchases: subscriptions and one-time buys. When we dug into the data, we found a significant pattern. Only 18% of one-time buyers made a second purchase. But if they did, there was an 85% chance they’d order a third time, and the repeat order rate stayed high after that. This showed us a major bottleneck. The founder initially wanted to focus all incentives on attracting first-time buyers, but the data told a different story. We saw the value in driving that crucial second purchase. So, we overhauled our approach: 1. Revamped Fulfillment Kits: The first order kit included incentives for a second purchase. 2. Updated Email Campaigns: Emails were tailored to encourage a second buy. The results? We boosted the second purchase rate to nearly 30%, leading to a significant increase in overall sales and customer lifetime value (LTV). Even with pushing more people into that second order, we only saw a small dip in the number of people who went from a 2nd to a 3rd order, moving from 85% to 83%. This experience shows the power of slicing your data by cohorts to uncover bottlenecks and then addressing them directly. Sometimes, the biggest gains come from focusing on the steps beyond the initial sale.