Guessing won't help: Why should you analyze “no results” queries in analytics

If you work with an online store, google analytics is your faithful companion that knows how much visitors your site has and therefore how much  your company makes. There is some functionality that will be useful to you. Your competitors probably haven’t thought about it. Analyzing “no results” queries in your analytics will help you to make your future income and compile a list of in-demand products. Western marketers have been using this data to drive their sales for ages. It's time for us to learn from the experience of leading experts.

There are three reasons to look at the “no results” queries report:

1. to track demand and replenish the assortment with popular items;

2. to learn timely about trends in your niche and stay ahead of competitors;

3. to predict the possible revenue from replenishing the assortment with new products.

How to make but not to lose $21,000. Let's look at a real example

You see a monthly report from an online pharmacy’s analytics. It deals with the internal search function and all the associated “no results” queries. Using one request as an example, we will show how you can lose $21,000 of income. And if you analyze the top 20 of ‘no result’ queries, the amount will double at least.

Formula: Number of not found queries * Product cost * CR conversion rate * 0.01 = Revenue

If you know all the values in the formula, it will be very easy for you to calculate the possible income from “no results” queries:

• number of “moisturizing care with high hydrabio content” requests with no results = 15,000 times;

• product price = $20;

• CR Conversion Rate —  Internal Site Search Conversion = 7%.

Here we go:

15,000 * 20 * 7 * 0.01 = 21,000 US dollars

The fact that the query was used so often tells us about the high demand for that product. It would be criminal not to add it to the assortment.
Why do you need Multisearch analytics when you have Google Analytics?

Multisearch.io analytics is a powerful tool that supports website sales. It allows you to keep track of what your customers are looking for and also what they didn’t find. It will keep track of the frequency of such requests. In addition to queries without results, this functionality also allows you to track search , transitions to products, categories, auto suggestions, corrected queries and other data. That is how you can see what products were searched in the online store and what products your customers associated with them. Multisearch's analytics are quite detailed, because we love to study its reports ourselves and monitor trends in various ecommerce niches.

What does Multisearch analytics show?

• all search operations - how many times a query was entered, how many clicks and how many times filters were applied. Example: search - 103130 times, 56.2%; transitions - 44040 times, 24%; filtration - 36238 times, 19.8%;

• found / not found - percentage of found and not found search queries. Example: found - 90.5%; not found - 9.5%;

• corrections - the percentage of requests written and corrected correctly. Example: no errors - 89.5%; typos - 7%; incorrect keyboard layout - 3.5%;

• direct transitions - request transitions from the search by quantity and percentage. Example: categories - 9719 times, 60.6%; brands - 3100 times, 19.3%; filters - 2458 times, 15.3%; goods - 771 times, 4.8%;

• clicks on tips - how many times and which tips were clicked, the number of specified requests. Example: query hints - 10311 times, 78.9%; categories - 1294 times, 9.9%; goods - 1163 times, 8.9%; clarification of requests - 301 times, 2.3%;

• queries with result - list and number of found queries. Example: the query "toys" was found 1351 times;

• requests with no result - list and number of not found queries. Example: "lego brickheadz" was searched 87 times;

• product transitions - the number of transitions to a specific product. Example: the resource "Samsung Galaxy J8 mobile phone" was visited 91 times;

• transitions in a category - the number of transitions to a product category. Example: the category "Mobile phones" was switched 520 times;

• clicks on filter categories - the number of clicks on the filter category. Example: the category "Mobile Phones" was clicked 1388 times;

• correction of mistakes - what mistakes and how many times were made in requests. Example: revised query "accumulator 3.7", original query "accumulator 3.7", count 173 times;

• correction of incorrect keyboard layout - which queries with the wrong layout and how many times were searched. Example: corrected query "iphone xs", original query "shzrshtu chy", number 96 times.

Multisearch is your friend and can help you maintain customer trust and become the best in your business. Analytics are available in all smart and fast search packages. High conversions for you!