Owners of online stores and SEO specialists often face a situation when it’s almost impossible to quickly get into the top of search results for high-frequency target queries. This happens most often due to strong competition.
This is the picture we saw when promoting the website of Bosch Aerotwin car wipers online store. It’s a relatively young resource developed by our agency. This article will tell you how we optimized for low-frequency keywords to avoid this problem.
Prerequisites
From the very start, Bosch Aerotwin store chose a niche quite successfully. It specialized in selling not just car wipers, but only one brand – Bosch, focusing on its most up-to-date product line Aerotwin. Due to this, it was possible to achieve the top in Google Ukraine for such branded queries as "buy bosch aerotwin" or "bosch aerotwin wipers" quickly. However, the situation was not so good with queries that are more general.
Google SERP for "buy bosch aerotwin" with store's site on the first position
Bosch Aerotwin store doesn’t have many direct competitors (online stores selling only car wipers in Ukraine). However, to get to the top of search results, it had to compete not only with them. A significant part of SERP for requests like "cars wipers" is occupied by large auto parts stores that have a huge range of goods and strong link profiles.
Pages that refer to wiper blades on these large sites are often less optimized and contain less useful content than in specialized wiper stores. However, these sites win because of their general "weight", so it’s not easy to overtake them by high-frequency queries ("wipers", "buy wipers", "car wipers").
Methods
We assumed that competition with large online stores can be avoided by using low-frequency queries. In the niche of car wipers, there are plenty of them. These are keywords related to wipers for certain car models ("reno traffic wipers", "buy wipers for chevrolet aveo", "rear wiper skoda octavia a5"). Marketplaces offering a wide range of auto parts are unlikely to optimize for these queries, as the wipers do not form the basis of their sales.
Similar queries section in Google for "skoda octavia a5 wipers"
We collected the semantic core for analysis basing on the site’s content. First, we used Screaming Frog SEO Spider to parse titles of the catalog pages. From these titles, we extracted the base of all car models for which the store sells wipers. Having added to the name of each car "wipers for ...", we received a primary set of queries.
Screaming Frog SEO Spider report with titles of catalog pages
Then we expanded the semantics using Key Collector. After filtering out unnecessary keywords, as well as words with zero frequency by Google Ads, we received a list of 550 queries that we used. Most of keywords from the list had a frequency near 10-20 requests per month by Google Ukraine; however, for some of the most popular cars, it reached 140 requests per month ("wipers for lanos").
Final queries list in Key Collector sorted by frequency in Google Ukraine
We checked the site's positions for all the keywords from the array, and then selected first of all those pages that are already ranked by a sufficient number of target keywords (at least 4 per page), but mostly in the top 20-30, so pushing them into the top 10 seems like a challenge. We optimized these pages first. We also paid attention to the cannibalization of keywords, which had to be eliminated (for example, if a Mazda 3 catalog page was ranked by the query "wipers for mazda 6").
Seranking statistics for Mazda 3 page. Average postitions before and after optimization are highlighted. You can also see 6 targeted queries, their frequences and page's positions by them
Before optimizing, car model pages contained:
- first and second level headers;
- links to product cards suitable for this car with photos and brief specifications;
- occasionally – a brief reference about the unique features of the wipers for this car;
- customer reviews (if customers made them for this model).
As you can see, the text content on the pages was rather poor, so we first decided to add a small text (1000-1500 characters) under the product photo. The text contained:
- brief general information about the car model;
- general characteristics of wipers suitable for it (size, type of attachment);
- options for wipers that are offered for this car, and recommendations on how to choose the right one;
- if necessary – some issues that are worth paying attention to not make a mistake when choosing wipers;
- occurrences of targeted keywords.
An example of a car model page with optimized text
Results
For now, we have optimized 28 pages of car models. Texts were added in several stages, so a different time has passed since the modification for different pages. For visual comparison we consider positions after 1 month and, if available, after 2 months. You can see our results in the table below.
Car model |
Average position before optimization |
Average position after 1 month |
Average change after 1 month |
Average position after 2 months |
Average change after 2 months |
Changes date – August 9, 2018 |
|||||
Ford Focus II |
25 |
7 |
+18 |
7 |
+18 |
Ford Focus III |
29 |
14 |
+15 |
10 |
+19 |
Mitsubishi Lancer IX |
27 |
18 |
+9 |
11 |
+16 |
Opel Astra J |
15 |
8 |
+7 |
7 |
+8 |
Skoda Octavia A5 |
7 |
5 |
+2 |
4 |
+3 |
ВАЗ 2110-2112 |
40 |
37 |
+3 |
34 |
+6 |
Lada Priora |
>100 |
30 |
+70 |
26 |
+74 |
Volkswagen Tiguan |
13 |
13 |
0 |
12 |
+1 |
Changes date – September 13-14 2018 |
|||||
Chevrolet Aveo |
32 |
16 |
+16 |
|
|
Citroen C4 |
21 |
14 |
+7 |
|
|
Kia Ceed |
74 |
26 |
+48 |
|
|
Mazda 3 |
23 |
13 |
+10 |
|
|
Mazda 6 |
20 |
14 |
+6 |
|
|
Mazda CX5 |
23 |
12 |
+11 |
|
|
Mitsubishi Outlander |
31 |
10 |
+21 |
|
|
Nissan Qashqai |
22 |
12 |
+10 |
|
|
Opel Astra H |
41 |
25 |
+16 |
|
|
Volkswagen Passat B5 |
14 |
15 |
-1 |
|
|
Volkswagen Polo |
26 |
24 |
+2 |
|
|
Suzuki SX4 |
11 |
6 |
+5 |
|
|
Renault Traffic III |
26 |
34 |
-8 |
|
|
Skoda Fabia |
46 |
28 |
+18 |
|
|
Hyundai Accent |
37 |
28 |
+9 |
|
|
Changes date – September 27 2018 |
|||||
Daewoo Lanos |
30 |
26 |
+4 |
|
|
Hyundai Getz |
14 |
11 |
+3 |
|
|
Audi A4 Avant |
30 |
19 |
+11 |
|
|
Toyota Camry 40 |
19 |
12 |
+7 |
|
|
Toyota Corolla |
17 |
17 |
0 |
|
|
Thus, we can see that to optimize text for a number of low-frequency queries was enough to increase positions in Google significantly. For some queries, we were able to hit top 10. Mostly these were the pages that ranked in top 20 before optimization.
In addition, text optimization helped to avoid the cannibalization of keywords. For example, a week after changing and indexing the page of Opel Astra J, we noticed that it began to rank also by queries related to Opel Astra H (there was no text on the page of this model). After we optimized the Opel Astra H page, it returned the necessary target queries to itself. We had a similar situation with the Volkswagen Polo page: before optimization, Volkswagen Golf and Passat pages ranked for a number of keywords related to this model.
We can also note that the most active growth of positions occurred during the first month after optimization. However, during the second month we observed further growth too.
Some of the optimized pages did not show an increase in positions or even showed a slight decline. In the case of Daewoo Lanos and VAZ 2110-2112, this can be explained by the relatively high frequency of target queries: maybe competitors also promoted on these keywords, so text optimization was not enough. For Toyota Corolla, Renault Traffic and Volkswagen Passat, the lack of growth may be due to an insufficient time since the moment of changes or due to random search result fluctuations that are not dependent on our efforts.
Conclusions
Thus, text-based page optimization has shown itself to be quite an effective method of promoting online car wipers store for low-frequency queries. A number of pages have already achieved good results due to the addition of text; for others, this manipulation was not enough. Most likely, further growth of the positions for such pages can be achieved through link promotion.