What does Pricecharting.com Product Collection Price History Scraper do?

The Pricecharting.com Product Collection Price History Scraper is a specialized tool that allows you to extract detailed product collection price history data directly from the Pricecharting.com platform. It provides comprehensive product collection price history information in structured formats like JSON, which you can easily integrate into your reports, spreadsheets, or applications.

With this scraper, you can:

• Extract detailed product collection price history information from Pricecharting.com.
• Access data in structured formats like JSON for seamless integration and analysis.
• Collect comprehensive product collection price history details from all countries where Pricecharting operates.

The scraper allows you to collect comprehensive product collection price history information, including:

• URL
• Title
• Chart Data
• From URL

Input & Output

To start collecting Pricecharting product collection price history data, simply fill out the input form. Pricecharting.com Product Collection Price History Scraper recognizes the following input parameters:

• URLs - Links to product collection price history information pages. You can paste URLs one at a time or use the Bulk Edit section to add a prepared list.
• Limit the number of retries - Maximum number of retries for each URL when collecting data when an unexpected error occurs.
• Proxy configuration - Add a proxy to ensure that during the data collection process, you are not detected as a bot.

Collect product collection price history data from product collection price history information pages

Example url: https://www.pricecharting.com/console/pokemon-promo

Example Screenshot of product collection price history information page:

Input:

1{
2  "max_retries_per_url": 2, // Maximum waiting time when accessing the links you provided.
3  "proxy": { // Add a proxy to ensure that during the data collection process, you are not detected as a bot.
4    "useApifyProxy": true,
5    "apifyProxyGroups": [
6      "RESIDENTIAL" 
7    ],
8    "apifyProxyCountry": "SG" // You should choose an Country that coincides with the Country you want to collect data from
9  },
10  "urls": [ // Links to product collection price history information pages.
11    "https://www.pricecharting.com/console/pokemon-promo"
12  ]
13}

Output:

You get the output from the Pricecharting.com Product Collection Price History Scraper stored in a tab. The following is an example of the Information Fields collected after running the Actor.

1[ // List of product collection price history information
2  {
3    "url": "https://www.pricecharting.com/console/pokemon-promo",
4    "title": "Prices for Pokemon Promo Pokemon Cards",
5    "chart_data": {
6      "median": [
7        [
8          "2021-02-03 00:00:00+00:00",
9          508
10        ],
11        [
12          "2021-03-03 00:00:00+00:00",
13          487
14        ],
15        [
16          "2021-04-03 00:00:00+00:00",
17          493
18        ],
19        [
20          "2021-05-03 00:00:00+00:00",
21          463
22        ],
23        [
24          "2021-06-03 00:00:00+00:00",
25          441
26        ],
27        [
28          "2021-07-03 00:00:00+00:00",
29          429
30        ],
31        [
32          "2021-08-24 18:05:58+00:00",
33          417
34        ],
35        [
36          "2021-09-03 19:55:27+00:00",
37          420
38        ],
39        [
40          "2021-10-02 02:05:02+00:00",
41          400
42        ],
43        [
44          "2021-11-02 08:04:54+00:00",
45          435
46        ],
47        [
48          "2021-12-02 09:05:02+00:00",
49          470
50        ],
51        [
52          "2022-01-03 00:00:00+00:00",
53          480
54        ],
55        [
56          "2022-02-02 09:05:06+00:00",
57          482
58        ],
59        [
60          "2022-03-10 17:26:40+00:00",
61          496
62        ],
63        [
64          "2022-04-02 08:02:59+00:00",
65          481
66        ],
67        [
68          "2022-05-02 08:02:55+00:00",
69          482
70        ],
71        [
72          "2022-06-02 08:02:50+00:00",
73          497
74        ],
75        [
76          "2022-07-02 08:03:00+00:00",
77          475
78        ],
79        [
80          "2022-08-02 08:03:03+00:00",
81          461
82        ],
83        [
84          "2022-09-02 08:02:59+00:00",
85          463
86        ],
87        [
88          "2022-10-02 08:02:48+00:00",
89          467
90        ],
91        [
92          "2022-11-02 08:03:04+00:00",
93          455
94        ],
95        [
96          "2022-12-02 09:03:11+00:00",
97          463
98        ],
99        [
100          "2023-01-02 09:03:20+00:00",
101          457
102        ],
103        [
104          "2023-02-02 09:03:21+00:00",
105          496
106        ],
107        [
108          "2023-03-02 09:03:43+00:00",
109          475
110        ],
111        [
112          "2023-04-02 08:03:44+00:00",
113          461
114        ],
115        [
116          "2023-05-02 08:03:32+00:00",
117          455
118        ],
119        [
120          "2023-06-02 08:03:46+00:00",
121          449
122        ],
123        [
124          "2023-07-02 08:03:38+00:00",
125          438
126        ],
127        [
128          "2023-08-02 08:04:07+00:00",
129          428
130        ],
131        [
132          "2023-09-02 08:03:45+00:00",
133          415
134        ],
135        [
136          "2023-10-02 08:03:35+00:00",
137          412
138        ],
139        [
140          "2023-11-02 08:03:46+00:00",
141          400
142        ],
143        [
144          "2023-12-02 09:03:53+00:00",
145          423
146        ],
147        [
148          "2024-01-02 09:03:25+00:00",
149          418
150        ],
151        [
152          "2024-02-02 09:03:36+00:00",
153          464
154        ],
155        [
156          "2024-03-02 09:03:55+00:00",
157          424
158        ],
159        [
160          "2024-04-02 08:03:34+00:00",
161          419
162        ],
163        [
164          "2024-05-02 08:03:38+00:00",
165          422
166        ],
167        [
168          "2024-06-02 08:03:35+00:00",
169          425
170        ],
171        [
172          "2024-07-02 08:03:55+00:00",
173          435
174        ],
175        [
176          "2024-08-02 08:04:12+00:00",
177          400
178        ],
179        [
180          "2024-09-02 08:03:58+00:00",
181          399
182        ],
183        [
184          "2024-10-02 08:03:48+00:00",
185          401
186        ],
187        [
188          "2024-11-02 08:04:02+00:00",
189          400
190        ],
191        [
192          "2024-12-02 09:04:00+00:00",
193          399
194        ],
195        [
196          "2025-01-02 09:03:50+00:00",
197          407
198        ]
199      ],
200      "value": [
201        [
202          "2021-02-03 00:00:00+00:00",
203          1567
204        ],
205        [
206          "2021-03-03 00:00:00+00:00",
207          1739
208        ],
209        [
210          "2021-04-03 00:00:00+00:00",
211          1716
212        ],
213        [
214          "2021-05-03 00:00:00+00:00",
215          1635
216        ],
217        [
218          "2021-06-03 00:00:00+00:00",
219          1411
220        ],
221        [
222          "2021-07-03 00:00:00+00:00",
223          1437
224        ],
225        [
226          "2021-08-24 18:05:58+00:00",
227          1376
228        ],
229        [
230          "2021-09-03 19:55:27+00:00",
231          1403
232        ],
233        [
234          "2021-10-02 02:05:02+00:00",
235          1397
236        ],
237        [
238          "2021-11-02 08:04:54+00:00",
239          1335
240        ],
241        [
242          "2021-12-02 09:05:02+00:00",
243          1352
244        ],
245        [
246          "2022-01-03 00:00:00+00:00",
247          1435
248        ],
249        [
250          "2022-02-02 09:05:06+00:00",
251          1403
252        ],
253        [
254          "2022-03-10 17:26:40+00:00",
255          1539
256        ],
257        [
258          "2022-04-02 08:02:59+00:00",
259          1505
260        ],
261        [
262          "2022-05-02 08:02:55+00:00",
263          1505
264        ],
265        [
266          "2022-06-02 08:02:50+00:00",
267          1556
268        ],
269        [
270          "2022-07-02 08:03:00+00:00",
271          1543
272        ],
273        [
274          "2022-08-02 08:03:03+00:00",
275          1557
276        ],
277        [
278          "2022-09-02 08:02:59+00:00",
279          1561
280        ],
281        [
282          "2022-10-02 08:02:48+00:00",
283          1499
284        ],
285        [
286          "2022-11-02 08:03:04+00:00",
287          1467
288        ],
289        [
290          "2022-12-02 09:03:11+00:00",
291          1749
292        ],
293        [
294          "2023-01-02 09:03:20+00:00",
295          1520
296        ],
297        [
298          "2023-02-02 09:03:21+00:00",
299          1524
300        ],
301        [
302          "2023-03-02 09:03:43+00:00",
303          1454
304        ],
305        [
306          "2023-04-02 08:03:44+00:00",
307          1453
308        ],
309        [
310          "2023-05-02 08:03:32+00:00",
311          1456
312        ],
313        [
314          "2023-06-02 08:03:46+00:00",
315          1457
316        ],
317        [
318          "2023-07-02 08:03:38+00:00",
319          1469
320        ],
321        [
322          "2023-08-02 08:04:07+00:00",
323          1462
324        ],
325        [
326          "2023-09-02 08:03:45+00:00",
327          1471
328        ],
329        [
330          "2023-10-02 08:03:35+00:00",
331          1448
332        ],
333        [
334          "2023-11-02 08:03:46+00:00",
335          1413
336        ],
337        [
338          "2023-12-02 09:03:53+00:00",
339          1403
340        ],
341        [
342          "2024-01-02 09:03:25+00:00",
343          1415
344        ],
345        [
346          "2024-02-02 09:03:36+00:00",
347          1486
348        ],
349        [
350          "2024-03-02 09:03:55+00:00",
351          1433
352        ],
353        [
354          "2024-04-02 08:03:34+00:00",
355          1602
356        ],
357        [
358          "2024-05-02 08:03:38+00:00",
359          1587
360        ],
361        [
362          "2024-06-02 08:03:35+00:00",
363          1600
364        ],
365        [
366          "2024-07-02 08:03:55+00:00",
367          1604
368        ],
369        [
370          "2024-08-02 08:04:12+00:00",
371          1709
372        ],
373        [
374          "2024-09-02 08:03:58+00:00",
375          1685
376        ],
377        [
378          "2024-10-02 08:03:48+00:00",
379          1659
380        ],
381        [
382          "2024-11-02 08:04:02+00:00",
383          1656
384        ],
385        [
386          "2024-12-02 09:04:00+00:00",
387          1659
388        ],
389        [
390          "2025-01-02 09:03:50+00:00",
391          1658
392        ]
393      ]
394    },
395    "from_url": "https://www.pricecharting.com/console/pokemon-promo"
396  }, // ... Many other product collection price history details
397]

How can I use the data extracted from Pricecharting with Pricecharting.com Product Collection Price History Scraper?

💙 Increase Brand Awareness: Leverage the data to boost your brand's visibility and recognition on Pricecharting.com and other platforms.

📈 Analyze Trends and Market Influences: Track and analyze emerging trends in product collection price history categories, brands, and sellers to maintain a competitive advantage in the market.

🔬 Fuel Research and Testing: Use the extracted data for in-depth research and testing, helping you refine strategies or develop new product collection price history products.

⭐ Enhance Sentiment Analysis: Count and score authentic reviews of product collection price histories to strengthen sentiment analysis with accurate and reliable data.

🪧 Plan Data-Driven Commercial Campaigns: Create impactful commercial campaigns for Pricecharting.com or other sales platforms, using data-driven insights to drive growth.

📚 Simplify Market Research: Streamline your market research efforts and enhance your marketing strategies with actionable insights from Pricecharting.com.

📋 Generate Targeted Marketing Leads: Build a list of perfectly matched marketing leads to optimize outreach and improve conversion rates.

Your feedback

We are always working to improve Actors' performance. So, if you have any technical feedback about Pricecharting.com Product Collection Price History Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.