SEO | Collection of semantic core and its clustering for Ukraine (Veterinary niche)

1. Short project description

Project: PetsCare — an online platform (veterinary hub) for pet owners, clinics, veterinarians, and pet stores.
Geo-target: Ukraine
Language: Ukrainian
Goals:

• To gather the widest possible semantic core covering commercial, informational, geographical, and brand queries in the veterinary and pet goods niche.
• To structure (cluster) it according to the best SEO practices.
• To obtain three final files (dirty core, clean core, and clustered core).

2. Requirements for the semantic core

1. Size and completeness

   • The semantics must be as broad as possible to cover the key needs of users in the veterinary field.
   • Not to be limited to high-frequency queries; important mid-frequency and low-frequency (long-tail) queries, as this provides better accuracy and coverage.

2. Brand queries

   • Must include brands of veterinary companies: clinics, centers, stores, pet salons, pet hotels, etc. (all popular and regional).
   • Brands of pet product and medication manufacturers (Ukrainian and international, if they are used in Ukraine; example: “Каніверм”, “Frontline”, “Royal Canin”, etc.).

3. Informational queries

   • A significant portion of queries should be informational: care tips, disease symptoms, feeding regimes, vaccination, prevention, lists of veterinary medications and their applications, etc.
   • The thematic spectrum is wide: from “how to choose food” to “how to vaccinate a cat” or “how to treat worms in dogs”.

4. Geographical (GEO) queries

   • The semantics must cover names of Ukrainian cities and regions: Kyiv, Lviv, Kharkiv, Dnipro, Odesa, Zaporizhzhia, Vinnytsia, etc.
   • Combine geo with veterinary services/brands (for example, “veterinary clinic Kyiv”, “veterinarian Dnipro”, “pet store Lviv”).
   • Consider forms of queries with shortened names or misspellings (if necessary).

5. Service queries

   • List all types of services that clinics and veterinarians can provide (surgery, vaccination, microchipping, dentistry, ultrasound, X-ray, etc.).
   • Include “questions-answers” (for example, “how much does cat sterilization cost in Kyiv”).

6. Sources

   • Use specialized tools (for example, Key Collector, Serpstat, Ahrefs, SEMrush, Google Keyword Planner) to collect keys and extract frequency.
   • Check Google suggestions (autocomplete), “Related searches” and other sources to identify additional keys.

7. Structure and format

   • Each key query must contain search frequency on Google in Ukraine (average or more precise, depending on the tool).
   • If possible, indicate Keyword Difficulty (difficulty of promotion) — a metric of the tool.
   • Consider synonymous and morphological variants (taking into account the Ukrainian language).

3. Clustering

After collecting the keyword base (dirty semantics), it is necessary to conduct cleaning (removal of duplicates, irrelevant, spammy, or foreign queries). Then it is necessary to cluster the keys into the following groups:

1. Informational clusters

   • Queries in the format of “how”, “why”, “how much”, “what to do if…”, symptoms, tips, FAQ, etc.
   • Example: “how to treat ringworm in a cat”, “how many times a day to feed a kitten”.

2. Commercial clusters

   • Queries related to the purchase of services/products: “buy dog food”, “24-hour veterinary clinic”, “call a veterinarian at home”.
   • Include direct brand queries with words like “order”, “buy”, “sign up”, “price”, “cost”.

3. GEO (location) clusters

   • Combining veterinary queries with geography: “veterinarian Kyiv left bank”, “pet store in Lviv center”, “veterinary clinic Odesa Primorsky district”.
   • Also brand+city: “veterinary clinic Aibolit Kharkiv”, “pet store MasterZoo Ivano-Frankivsk”, etc.

4. Brand clusters

   • Specific names of veterinary networks, clinics, product brands: “Royal Canin buy Ukraine”, “Zoetis vaccines”, “Pet hotel Miau Odesa”, etc.
   • Can be divided into “service brands” (clinics, salons) and “product brands” (food, medication manufacturers).

5. (If necessary) Additional clusters

   • If groups of keys are found that do not fit into the main categories, they can be highlighted separately (for example, “forum queries”, “veterinary associations”, etc.).

4. Format and structure of output files

1. File “Dirty semantics” (Dirty semantic)

   • All collected keys without removal of duplicates and without filtering.
   • XLSX/CSV format with the following fields:
     • key (key phrase),
     • average search frequency in Google UA (volume),
     • Keyword Difficulty (KD) — if possible.

2. File “Clean semantics” (Clean semantic)

   • This same list of keys after cleaning, without duplicates or irrelevant queries.
   • XLSX/CSV format with the following fields:
     • key,
     • search volume,
     • KD.

3. File “Clustered semantics” (Clustered semantic)

   • The same keys, but with added fields:
     • key,
     • search volume,
     • KD,
     • group name (for example, “informational”, “commercial”, etc.),
     • cluster (specific name, for example, “sterilization”, “vaccination”, “buy food”, etc.).
   • The essence is that the “group name” reflects the top level (informational, commercial, geo, brand), while the “cluster name” specifies the topic (for example, “dog vaccination”, “cat sterilization”, “pet hotel in Kyiv”, etc.).

5. Additional requirements and recommendations

1. Relevance check

   • The performer should remove irrelevant keys to the veterinary topic (for example, if queries about unrelated services or other fields are pulled).

2. Processing long tails

   • Pay special attention to “long-tail” queries (question phrases, unique combinations, specific services), as they can provide targeted traffic with high conversion.

3. Consider seasonality

   • If possible, pay attention to seasonal fluctuations (for example, increased demand for vaccination and parasite treatment in the spring-summer period).
   • It can be marked when the peak frequency occurs if the tool provides such information.

4. Consider the specifics of Ukrainian regions

   • If there are local peculiarities in the spelling of names or brand positioning in certain regions, they should be included (for example, “Kyiv” vs “Kyiv region”, or dialectal name variants for western regions).

5. Use modern SEO practices

   • Ensure that the semantics include synonyms, word forms (plural/singular, different cases).
   • It is also advisable to consider LSI queries (lexical-semantic similarity, to make the content more diverse).
   • If possible, group informational queries and prepare “article ideas” (content topics) to make it easier to form a content plan later.

6. Criteria for completion of work

   • The semantic core of all necessary types (commercial, informational, geo, brands).
   • Three files described above, with complete fields (key, frequency, KD, group/cluster).
   • A report on the tools and approaches used (a brief description of which services were used, how frequency was extracted, etc.).

6. Submission format

1. XLSX/CSV file with “dirty” semantics.
2. XLSX/CSV file with “clean” semantics.
3. XLSX/CSV file with “clustered” semantics (according to groups and cluster names).
4. A brief text report (PDF/DOCX) on how the collection and clustering were conducted, which tools were used, which main groups of keys turned out to be the most numerous.

7. Feedback on this task

1. Experience for you this is not your first job with semantics.
2. Software/services you have the necessary software or subscriptions to services.
3. Example You send one or two examples of completed clustering (can be 10-20 clusters, no need for the entire core).

IMPORTANT!!! You should not write just anything, you will end up on a blacklist, read carefully and think whether you enjoy this work and task!

In your response, write:

• Whether everything is clear,
• What the approximate deadline for the work is,
• What software/services will be used by you,
• An example of your work.