In this vast ecology of treasure hunting, the ability of buyers to search for goods with precision is directly related to the flow and transformation of shops. One of the core elements of the search optimization is the keyword strategy. In addition to highly competitive head words, long-term keywords often have great potential. Their search intentions are clear, competition is relatively small and conversion rates are higher. Today, we're going to explore the use of treasure-searching api for high-impact long-term excavations and the promotion of seo at the power shop。
I. Why is the long end so important
Precision matching user needs: long end words usually consist of multiple words (e. G., "summer air-breeding net men's sneakers") that more accurately reflect the user's search intentions。
The level of competition is relatively low: the level of competition for long endings is usually much lower than for hot words such as “sports”, “men's shoes” and it is easier for new shops or small and medium-sized sellers to be presented。
The rate of conversion is higher: searching for long-term end-word buyers is more purposeful and more explicit and therefore has greater potential for transformation。
Disaggregated markets were found: analysis of long-term endwords led to the identification of unsatisfied sub-demands or emerging trends。
Ii. Treasure search api: technical core for digging long end words
The open platform provides a rich api interface in which search-related api is a powerful tool for digging long lines. The core principle is that when we send api a "seed word" (e. G. "shoes"), api returns information about the word, the hot word and the list of goods. These returned data contain a large number of valuable long end-word variants。
Basic workflow:
Api call: use taobao. Tbk. Item. Get or similar search-related api (specific interface requires access to up-to-date documents) and upload core keywords as request parameters。
Data acquisition: api returns usually include:
Keyword or word list: relevant search keyword list (this is the main source of long end words)。
Relaid keywords: related keywords。
The title information in the list of goods (which can be extracted by further crosswords)。
Data processing: cleaning, phraseing, filtering, counting of returned keyword lists。
Purge: remove invalid characters, repeat words。
Division of words: the combination of words is divided into more fine words using a semantic tool (e. G. Jieba)。
Filtering: screening based on terminological (nouns, adjectives), length, specific business rules (e. G. Excluding brand names)。
Statistics: calculate the frequency of words, the frequency of occurrence of combinations, etc. The significance of word frequency can be expressed in formulae: $$text{syllable}(w)=frac{text{word} wtext{number of times that appear in return result}} {text{total word} } $$ or consider the uniqueness of word combinations (reverse document frequency idea): $$text{w)propto logfr{text{total commodity number}} {text{number of commodities that include } wtext{} +$ composite importance can be expressed as: $text{material} = text{digit}(w) times text{unique} $。
Long end words generation and assessment: a sifted word is reasonably combined to form a new long end word candidate. The assessment dimensions could include:
Search volume estimates (heat index or third-party tool returned through api)。
Competition analysis (see the number of commodities using the long endword)。
Commercial values (combining sub-category average prices, conversion rate experience values)。
Core logic example (python pseudocode):
I# for sending api requests
iMport jieba. Analyse# for crosswords and keyword extraction
i'm here to see youMport guinea# for word frequency statistics
# 1. Call for treasures searching for api (replaced for actual api urls and parameters, containing authentication information such as app key, sign)
i don't know, call taobao search api (seed keyword):
params = {
'method': 'taobao. Tbk. Item. Get', # example api method, practical confirmation
'fields': 'keyword, word list, type', # required fields
'q': seems keyword, # search word
# ... Other necessary parameters like app key, sign, timestamp
♪ i'm sorry ♪
respo= requests. Get ('https://api. Taobao. Com/router/rest', params=params)
data = return. Json()
# parsing back data, extracting list of keywords, list of commodity titles
♪ assume structure is so
# assume structure is so
now, look, look, look, look. 2. Data processing
= "sport shoes."
= call taobao search api (seed word)
# merge all text sources
all texts=suggested keywords+titles
# split words and extract keywords
all words =
for text in all texts:
# use jieba to extract keywords with weight
# tags = jieba. Analyse. Extract tags
# or simple words
words = jieba. Lcut (text)# precision mode semiwords
all words. Extend (words)
# word frequency statistics
word counter =counter (all words)
# filter: remove disabled words, words, etc.
{word: count for word, count in word counter. Items() if pen (word) > and word not in stops}
# sort by word frequency
sorted words = sorted (filed words. Items(), key=lambda x: x [1], reverse=true)
# 3. Long tail group generation (simplified example)
# high-frequency qualifiers: like 'breath', 'net', 'men', 'summer'
high freq modifiers = [word for word, count in received words [:50] if...] # further sifting by word type, etc. Select
# combine with seed words
long tail candidates = [f"{mod}s for mod in high freq modiffers] +
[f]'for mod in high freq modiffers]
# top 10 output
Iii. How do you upgrade the seo with the long end words that were excavated
Optimization of commodity titles: natural integration of high potential and relevant long end words into commodity titles. Watch for readability and avoid stacking。
Layout of commodity properties: in the properties fields of colour, material, style, applicable scenes, etc., use the feature words contained in long end words。
Enriched details: use long end words and their associated vocabulary naturally in commodity descriptions, sales outlets to increase page relevance。
Directs straight-to-car selection: adds high-quality excavated long end words to the straight-to-car plan to capture accurate flow at lower cost。
Content marketing options: creating content from buyer shows, microbrushes, live broadcasts, etc. Around the user issues behind the long end。
Iv. Practice cases and effects
A sports shoe store, using the api tool to dig up the long end words associated with "sport shoes," found that the long end words "sports in middle school boys running shoes" had a certain amount of search and competition for fewer goods. Optimize the word into the relevant commodity headings and attributes. A week later, the natural search flow brought about by the long end phrase increased by about 15 per cent and the conversion rate was significantly higher than that of commodities using “sport shoes” or “run shoes”。
V. Summary and recommendations
Good tools: the treasure-searching api is a powerful official data source, combining simple programming capabilities (or existing tools) to efficiently extract long words。
Overtime: user search behaviour changes, requiring regular (e. G. Monthly) re-excavation and analysis of long endings。
Data driver: do not make decisions based solely on the selection of the words, combining search volumes, competition, conversion rates。
Compliance: api must be used in accordance with the rules of the open platform and the restrictions on access。
Combining manual: technical excavation provides a candidate and final decision-making needs to be combined with product characteristics, market understanding and documentation。
Excavating long-term keywords through technical means and effectively applying them to commodity optimization and diffusion are important strategies for small and medium-sized sellers to achieve a flow breakthrough and seo upgrading in an environment of competition for treasures. Let's try it
Check and edit, huang woo
