You haven’t used TraQline this way before

We’ve polled our greatest account managers of all time (i.e. all of them) about the secret ways that they’ve worked with their customers to use TraQline. They highlighted methods beyond just looking at brand share, outlet share, and average price paid. Below is a collection of our favorite ways to use TraQline that you’re probably not doing!

Table of Contents:
1) Notes 1 & 2

2) Brand vs Brand – who wins in head to head? | David Garcia

3) Using Single Variables | Eric Voyer

4) Door-to-Door Analysis | Scott Adelman

5) Determining Impact of Price Perception | Brennan Callahan

6) Have Purchase Motivations Changed? | Cher Nelson

7) Create a Template | Eric Voyer

Note 1: Sample Size

As we dig into each of these examples, it’s important to remember the importance of sample size in any analysis you conduct—whether with TraQline or any other data source. While TraQline’s massive 600,000 completed consumer surveys provides a great base for analysis, slicing and dicing can lead to diminished sample sizes. Keep your eyes on the sample size, and (typically) make sure you’re working with a sample of at least 300. For help in understanding whether a sample size or proportion is significant, contact us!

Note 2: Creating an Index

In some cases and in some reports, you’ll hear us refer to creating an Index. Indexing is the process of comparing a measure to the mean and highlighting the magnitude of differences.
How to do it: Indexing is fairly simple. To calculate, divide the metric by the industry average. Here’s the formula: Index = Metric Average/Industry Average.
Example:
Industry average: female purchaser 50%
Metric Average: your brand 75%
Index = (75-50)/50

We love indexing because gives you some perspective not just about the absolute value of your data, but how different that value is from your competition’s data. For example, you may see that on average 25% of power drill purchases are made by women – a remarkably low number (because you instinctively indexed it to the 50/50 population mix in your head!). With that in mind, when you see that a power drill brand has 50% of its purchases made by women, you begin to see a unique strength of that brand.

In the words of the great Christopher Walken of Balls of Fury, “Enough talky talky, more data analysis!” Here we’ll present our reps’ favorite tools in no particular order:

Brand vs Brand – who wins in head to head? – David

Consumers have many choices when it comes to the brands they consider. But ultimately, they usually only purchase one brand. Using TraQline’s consideration rates and purchase behavior, you can compare brand vs brand shopping and purchase behaviors over time to see who wins. This is particularly useful if you’re comparing your brand to one of your competitors to see which of the two consumers prefer.

Using Single Variables – Eric

We are frequently interested in comparing two stores or brands head-to-head, for example whether someone shopped at either Lowe’s or Home Depot. But when we want to know If someone shopped at one AND the other, our standard “Outlet_Shopped_Multi” variable won’t work.

The secret to this analysis is the “Purchase Process Single” variables at the bottom of the interactive row or column variable lists.  On the surface, it may appear that these are the same variable as the ‘_Multi-‘ variables in the purchase process section above. However, these variables serve a different purpose. The difference between “Outlet Shopped Multi” and “Shopped Best Buy” is the Boolean expression “AND”.

When you select multiple outlets in the “_Multi” variables (such as “BrandConsidered_Multi”), it means “OR”. As an example, selecting “Best Buy”, “Walmart”, and  “Bed Bath & Beyond” in OutletConsidered_Multi means that the shopper must have indicated that they shopped at any of these three stores. Using the “Purchase Process Single” variables allows you to use “AND” expressions, thus allowing you to narrow your results.

Door-to-door Analysis- Scott

Comparing a regional player’s market share to national players’ shares can be misleading. After all, some retailers have no interest in playing in larger markets, so why should the larger market impact their overall share? For example, Menards, is a regional player located in the Midwestern states. Comparing their share nationally vs. a player like Lowe’s will show Menards severely lacking in total share. In cases like this, you may wish to complete a door-to-door analysis. This can be completed by using a filter on a particular geography, ensuring that only stores that have “doors” in a particular geography line up with others in the same area.  Sometimes you may wish to use the DMA_Market variable, while other times State or even Census Region will encompass all of the geographies you wish to evaluate.

Determining Impact of Price Perception – Brennan

Retail POS systems will never get to the “why” behind the consumers’ buy. Fortunately, TraQline’s consumer data collects information not only about why they buy at that retailer, but why they buy that product and why they buy that brand. In some cases, a retailer may suspect that pricing is impacting close rate…and ultimately share. By comparing walk rates and retailer pricing, this analysis can provide directional information about the importance of pricing to the consumer.

Have purchase motivations changed? – Cher

Focusing on the why behind the buy can be powerful, but TraQline can help you identify emerging trends in why consumers buy the products they buy. For example, during the great recession, Price was a much more significant reason for purchase then in 2018, while the economy is booming. Using the variable “Why Bought Brand Multi” can help you not only identify consumers buying habits in the current time period, but also look to see how those may have changed in the last 10 years. This can help you catch emerging or declining trends and adjust your messaging and merchandising accordingly.

Create a template  – Eric

Not all of our tips and tricks are specific analyses. One of our favorite tricks is using saved reports as a template. Many times, we’re working with many different options in the row or column and would like to create an aggregate, or we’re filtering on a specific region that is difficult to reproduce each time you log in. This is where we like to use a saved report to create a template.

Conclusion

TraQline is like an iceberg: most of what people see is Brand, Outlet, Average Price paid, and draw close. Under the surface is so much more that can help you understand why people buy and answer the deeper questions about what drives market share up or down. We hope you’ve enjoyed these tips and we hope the wheels are turning about some of the other types of analyses you can create with TraQline. If you want to brainstorm, we’re only an email, phone call, or quick chat away!