Making online advertising effective offline
How to improve one of the most effective advertising channels? We understand the example of a large online furniture store.
A significant amount of our customer’s sales comes from offline channels: the number of customers who order furniture by phone or buy it in the showroom reaches 60% (40% call the company, 20% come to the showroom). At the same time, the average bill for purchases by phone is 27 thousand rubles, for a personal visit - 40 thousand rubles. There are another 40% of people who shop on the store’s website, the average cost of which is 20 thousand rubles. Thanks to tuned analytics counters, we know everything about this audience. Therefore, for a long time, the question remained open to us: who are these 60% of the offline audience, for the attraction of which we spend 50% of the advertising budget every month (from 5 to 15 million rubles)?
We tried to find out on our own and used two methods of analytics.
1) Static call tracking. For each city where there is a branch, they bought a pool of phone numbers and placed them in different advertising channels. One was used for banner outdoor advertising, the second - for advertising on the radio, the third - in contextual advertising. Accordingly, when a client called the company, it became obvious what source of advertising brought him.
2) Unique code. Each visitor to the store’s website received a unique code (a set of numbers), which they had to call the company manager upon call. The code corresponded to a specific source of advertising and, thus, it became clear which one works best.
In the end, however, we were forced to abandon both methods. The first was too expensive and time-consuming. The effectiveness of the second was interfered with by the human factor: sales managers often forgot to clarify the buyer's code or entered it into the database with errors. At this time, call tracking services appeared, which are designed to study an audience that prefers offline communication channels. The service allowed to significantly save on the purchase of telephone numbers and made it possible to process the received data in automatic mode.
Thus, the brand continued the story of working with contextual advertising in Yandex.Direct with one such service, which provided the company with the necessary pool of numbers, and simultaneously removed the dependence on the human factor.
1) A bunch of offline and online
First of all, we found out how many potential buyers who called the company really reach the showroom. To do this, we analyzed the sales model, which develops according to the scenario: the client visits the site, selects the product he likes, then calls the store with clarifying questions. Having received the information of interest, he goes to the showroom in order to finally establish himself in the choice and make a purchase.
Thus, in order to find out the source of advertising, it was necessary to combine the phone numbers of completely strangers who called the company with the contacts of customers who reached the showroom. For some time this question remained open, but the answer to it also helped to find a call tracking service.
It automatically determines the phone number from which the client calls, no matter whether it is a city or mobile. This in itself is valuable information, but we did not understand how to use it to solve the task. Therefore, we went further and combined it with data on people who made a purchase in the showroom. The coincidence was about 90% and made it possible to identify sources of advertising that lead to the maximum number of end customers.
The case demonstrates how important it is to track calls and applications not only on the site, but also offline (showroom). After finding out which sources of advertising lead real buyers, you can decide how best to spend your marketing budget.
The next stage of the study concerned a deeper immersion in analysis. Marketers found that general requests for upholstered furniture, advertising campaigns for the colors of sofas and for some competitors in Yandex.Direct do not actually bring sales. Therefore, their budget was allocated in favor of effective campaigns on models of sofas and selling queries: “buy a sofa”, “order a sofa”. Along the way, we found out that the average check for “buy a sofa” is 20 thousand rubles, and “buy a cheap sale sofa” is 30 thousand rubles. Paradoxically, people who want to save on purchases and go on sales actually spend more.
2) Analysis of paid traffic at the Yandex.Direct keyword level
But just finding out which keywords work is not enough; you need to understand how much sales they bring. Thanks to the call tracking service, the brand found out that some requests bring a lot of orders through calls, but not enough from the site. For example, a large number of end customers call on inexpensive requests: “sofa shop”, “buy a sofa in a store”, “Atlanta sofa”. Distributing the budget for these requests from less efficient ones, the store increased the number of calls by 31%, reducing the cost of requests by 19%. At the same time, calls ended in sales, it was 27% more.
In general, thanks to the obtained analytics, the redistribution of the budget in favor of profitable keywords made it possible to increase the income of advertising campaigns in Yandex.Direct by 45%, with an overall cost reduction of 14%.
3) Low-level optimization in Yandex.Direct
The next step for Profitora’s specialists was to determine the profitable Yandex.Direct advertising placements. It turned out that special placement, although it costs more than guaranteed, was justified for a number of campaigns and allowed to increase the number of calls that bring sales by 24%, reducing their cost by 7%. At the same time, the total number of calls increased by 14%.
4) Study of the behavior of the calling audience. The
answer to the question of where to place an advertisement depends on the time of day.
Having identified the peaks of activity of calling customers, we learned at what time the conversion of orders from the site decreases. For example, the conversion to purchases through the basket from 19:00 to 20:00 is reduced by 31% relative to the average per day, however, the conversion to calls is increased by 35%. In this simple example, we see how call tracking data helped to avoid an error. At first glance, the right step would be to lower the advertising bid at this time, but given that few people in our market track calls and are aware of these patterns, the price of a click in Yandex.Direct during this period of time is steadily decreasing and customers are cheaper .
5) Analysis of the quality of work of employees
No optimization of advertising will help to get more sales if the level of service is lame. The brand wanted to find out how employees communicate with customers. However, the development of its own interface for the PBX was expensive, so the company took advantage of the solution of our call tracking operator, in the "My Account" which records of each call are stored. The store’s sales managers regularly listen to colleagues ’conversations, and if they find errors, send an e-mail to the supervisor, providing the letter with a detailed comment.
6) A / B tests
The result of the Yandex.Direct campaign depends on the ad texts. A / B tests helped to choose effective ones: analysts measured which texts brought the most “selling” calls. To do this, they prepared several versions of announcements with different phone numbers, and then, through the call tracking service, they tracked which one they call most often. Focusing on working texts, the store increased calls from Yandex. Direct by 8%.
Before cooperation with the call tracking service, the share of revenue that Yandex.Direct brought to the store was 20%, after installation, the channel’s share increased to 40%.
On the example of the case it is clearly seen how the return on advertising can grow if you carefully approach the evaluation of effectiveness. We always recommend that advertisers take a conscious approach to placement - try to monitor all sales channels and optimize advertising settings in accordance with business objectives. Now many categories of advertisers are redistributing budgets in favor of the channels that most successfully attract customers, and along with this task, their approaches to evaluating this effectiveness and optimizing advertising are evolving more actively. We see that in entire industries where most advertisers used to focus on clicks or, at best, achieve individual goals on the site, they are now building full-fledged sales funnels, taking into account different communication channels with customers and delayed conversions, and campaigns are customized based on your investment. This is an expected and very good trend for the market, which reinforces its development, ”the Yandex press service comments on the results achieved.
A significant amount of our customer’s sales comes from offline channels: the number of customers who order furniture by phone or buy it in the showroom reaches 60% (40% call the company, 20% come to the showroom). At the same time, the average bill for purchases by phone is 27 thousand rubles, for a personal visit - 40 thousand rubles. There are another 40% of people who shop on the store’s website, the average cost of which is 20 thousand rubles. Thanks to tuned analytics counters, we know everything about this audience. Therefore, for a long time, the question remained open to us: who are these 60% of the offline audience, for the attraction of which we spend 50% of the advertising budget every month (from 5 to 15 million rubles)?
We tried to find out on our own and used two methods of analytics.
1) Static call tracking. For each city where there is a branch, they bought a pool of phone numbers and placed them in different advertising channels. One was used for banner outdoor advertising, the second - for advertising on the radio, the third - in contextual advertising. Accordingly, when a client called the company, it became obvious what source of advertising brought him.
2) Unique code. Each visitor to the store’s website received a unique code (a set of numbers), which they had to call the company manager upon call. The code corresponded to a specific source of advertising and, thus, it became clear which one works best.
In the end, however, we were forced to abandon both methods. The first was too expensive and time-consuming. The effectiveness of the second was interfered with by the human factor: sales managers often forgot to clarify the buyer's code or entered it into the database with errors. At this time, call tracking services appeared, which are designed to study an audience that prefers offline communication channels. The service allowed to significantly save on the purchase of telephone numbers and made it possible to process the received data in automatic mode.
Thus, the brand continued the story of working with contextual advertising in Yandex.Direct with one such service, which provided the company with the necessary pool of numbers, and simultaneously removed the dependence on the human factor.
1) A bunch of offline and online
First of all, we found out how many potential buyers who called the company really reach the showroom. To do this, we analyzed the sales model, which develops according to the scenario: the client visits the site, selects the product he likes, then calls the store with clarifying questions. Having received the information of interest, he goes to the showroom in order to finally establish himself in the choice and make a purchase.
Thus, in order to find out the source of advertising, it was necessary to combine the phone numbers of completely strangers who called the company with the contacts of customers who reached the showroom. For some time this question remained open, but the answer to it also helped to find a call tracking service.
It automatically determines the phone number from which the client calls, no matter whether it is a city or mobile. This in itself is valuable information, but we did not understand how to use it to solve the task. Therefore, we went further and combined it with data on people who made a purchase in the showroom. The coincidence was about 90% and made it possible to identify sources of advertising that lead to the maximum number of end customers.
The case demonstrates how important it is to track calls and applications not only on the site, but also offline (showroom). After finding out which sources of advertising lead real buyers, you can decide how best to spend your marketing budget.
The next stage of the study concerned a deeper immersion in analysis. Marketers found that general requests for upholstered furniture, advertising campaigns for the colors of sofas and for some competitors in Yandex.Direct do not actually bring sales. Therefore, their budget was allocated in favor of effective campaigns on models of sofas and selling queries: “buy a sofa”, “order a sofa”. Along the way, we found out that the average check for “buy a sofa” is 20 thousand rubles, and “buy a cheap sale sofa” is 30 thousand rubles. Paradoxically, people who want to save on purchases and go on sales actually spend more.
2) Analysis of paid traffic at the Yandex.Direct keyword level
But just finding out which keywords work is not enough; you need to understand how much sales they bring. Thanks to the call tracking service, the brand found out that some requests bring a lot of orders through calls, but not enough from the site. For example, a large number of end customers call on inexpensive requests: “sofa shop”, “buy a sofa in a store”, “Atlanta sofa”. Distributing the budget for these requests from less efficient ones, the store increased the number of calls by 31%, reducing the cost of requests by 19%. At the same time, calls ended in sales, it was 27% more.
In general, thanks to the obtained analytics, the redistribution of the budget in favor of profitable keywords made it possible to increase the income of advertising campaigns in Yandex.Direct by 45%, with an overall cost reduction of 14%.
3) Low-level optimization in Yandex.Direct
The next step for Profitora’s specialists was to determine the profitable Yandex.Direct advertising placements. It turned out that special placement, although it costs more than guaranteed, was justified for a number of campaigns and allowed to increase the number of calls that bring sales by 24%, reducing their cost by 7%. At the same time, the total number of calls increased by 14%.
4) Study of the behavior of the calling audience. The
answer to the question of where to place an advertisement depends on the time of day.
Having identified the peaks of activity of calling customers, we learned at what time the conversion of orders from the site decreases. For example, the conversion to purchases through the basket from 19:00 to 20:00 is reduced by 31% relative to the average per day, however, the conversion to calls is increased by 35%. In this simple example, we see how call tracking data helped to avoid an error. At first glance, the right step would be to lower the advertising bid at this time, but given that few people in our market track calls and are aware of these patterns, the price of a click in Yandex.Direct during this period of time is steadily decreasing and customers are cheaper .
5) Analysis of the quality of work of employees
No optimization of advertising will help to get more sales if the level of service is lame. The brand wanted to find out how employees communicate with customers. However, the development of its own interface for the PBX was expensive, so the company took advantage of the solution of our call tracking operator, in the "My Account" which records of each call are stored. The store’s sales managers regularly listen to colleagues ’conversations, and if they find errors, send an e-mail to the supervisor, providing the letter with a detailed comment.
6) A / B tests
The result of the Yandex.Direct campaign depends on the ad texts. A / B tests helped to choose effective ones: analysts measured which texts brought the most “selling” calls. To do this, they prepared several versions of announcements with different phone numbers, and then, through the call tracking service, they tracked which one they call most often. Focusing on working texts, the store increased calls from Yandex. Direct by 8%.
Before cooperation with the call tracking service, the share of revenue that Yandex.Direct brought to the store was 20%, after installation, the channel’s share increased to 40%.
On the example of the case it is clearly seen how the return on advertising can grow if you carefully approach the evaluation of effectiveness. We always recommend that advertisers take a conscious approach to placement - try to monitor all sales channels and optimize advertising settings in accordance with business objectives. Now many categories of advertisers are redistributing budgets in favor of the channels that most successfully attract customers, and along with this task, their approaches to evaluating this effectiveness and optimizing advertising are evolving more actively. We see that in entire industries where most advertisers used to focus on clicks or, at best, achieve individual goals on the site, they are now building full-fledged sales funnels, taking into account different communication channels with customers and delayed conversions, and campaigns are customized based on your investment. This is an expected and very good trend for the market, which reinforces its development, ”the Yandex press service comments on the results achieved.