Datastreamer Data Pipelines for Unstructured Data Thu, 12 Dec 2024 20:20:13 +0000 en-US hourly 1 https://datastreamer.io/wp-content/uploads/2022/04/cropped-DATASTREAMER-2048x331-1-32x32.png Datastreamer 32 32 When Will My Company Outgrow Talkwalker? A Guide for Social Listening Products https://datastreamer.io/outgrowing-talkwalker-guide-for-social-listening-products/ Thu, 28 Nov 2024 17:42:14 +0000 https://datastreamer.io/?p=42131 For social listening products entering the market, Talkwalker’s APIs offer a foundational framework to bring the UI, familiar experience, and supporting APIs together.

The post When Will My Company Outgrow Talkwalker? A Guide for Social Listening Products appeared first on Datastreamer.

]]>

When Will My Company Outgrow Talkwalker? A Guide for Social Listening Products

By Tyler Logtenberg

Decemeber 2024 | 7 min. read

Table of Contents

Talkwalker Is An Ideal Initial Solution

For social listening products entering the market, Talkwalker’s APIs offer a foundational framework to bring the UI, familiar experience, and supporting APIs together. In the creation of other social listening products, these APIs become the source backbones of the platforms. Talkwalker’s APIs offer: multi-source data aggregation, basic enrichments, and an accessible taxonomy system.

Utilizing the APIs of another platform provides companies a way to integrate social and media data into their products, and leverage enrichment and search capabilities, without building a custom data pipeline from scratch. However, while Talkwalker meets the needs of many early-stage use cases, it’s often outgrown as companies mature and require greater flexibility, real-time data, and in-depth analysis capabilities.

Talkwalker’s API Capabilities: What It Can (And Can’t) Do For Scaling Companies

Before we can dive into an exploration of the “when”, we need to understand what it can and can’t do for scaling products. While Talkwalker provides basic social listening functionality, its constraints can become limiting as companies expand:

  1. Credit-Based Data Access: Talkwalker’s API operates on a credit-based system, meaning that data access is limited by credit availability. For high-frequency or high-volume data needs, companies may quickly hit credit limits, creating bottlenecks and additional costs as data needs grow.
  2. Rate Limits of 240 Calls per Minute: In the scaled industry, rate limits become a key technical limitation, and are often measured in calls per second. While Talkwalkers rate limits may be sufficient for basic monitoring, scaling platforms with higher volumes can quickly find these restrictive, especially during high-traffic events or crisis monitoring.
  3. Self-Managed Data Storage: Talkwalker doesn’t store API results, leaving companies responsible for their own data storage. This can become a significant burden for teams scaling beyond initial use cases, especially if they need both current and historical data at hand. Elements like trend prediction, influencer efforts, AI training, or even moderate analysis require large volumes of data.
  4. Export Limitations: Data export restrictions affect several key platforms, including Facebook, Instagram, LinkedIn, and Reddit. Additionally, metadata for Twitter and other sources is limited, often forcing companies to rely on separate APIs for richer insights. In some cases, the documentation of Talkwalker suggests going directly to different data sources outside of the Talkwalker platform!
  5. Limited Enrichments: Talkwalker does offer basic enrichments, including sentiment analysis, country filtering, basic image analysis, topics, and entity recognition. While these are helpful for early insights, they may fall short as companies seek more detailed or custom data tags, audience insights, or advanced sentiment scoring. They are also general enrichments common across the market, limiting scaling companies from creating product differentiation or customization.
  6. Time-Limited Search Results: The API’s search capabilities allow access only to the last 30 days of data, limiting long-term analysis and making it challenging to identify historical trends over time.
  7. Boolean Search Cap: With a cap of 50 boolean operands, Talkwalker’s search capabilities can be restrictive, especially for platforms seeking to conduct complex, multi-variable searches.

Key Indicators You’re Outgrowing Talkwalker

  1. Increasing Data Source Needs: Organizations may be able to work within Talkwalker’s source constraints, using around 6 categories of data, as startups. However, as companies move to the scale-up or growth stage, they often need access to a wider range of sources. Enterprise companies typically require access to about 16 source categories to meet comprehensive data coverage needs. For many, Talkwalker’s export limitations on major social media and review platforms restrict the breadth of insights they can provide, which becomes increasingly problematic with scale.

This table is specific to the Brand Monitoring industry focus, and showcases the size, requirements, and if they have outgrown Talkwalker. These metrics are an average and do not take into account pivots or niche specializations.

Company Size Bracket

Data Source Categories Required*

Likely Outgrown?*

Average Company Age*

0-50 (Startup)

6

No

1.8 years

51-150 (Scaler)

8

Yes

3.9 years

151-400 (Growth Leaders)

10

Yes

5.9 years

400+ (Market Titans)

16

Yes

8.8 years

*Specific to Brand Monitoring industry focus

  1. High Data Volume or Frequency Needs are Pushing Credit Limits: Companies with growing data needs often find themselves quickly depleting Talkwalker credits, particularly if they are pulling data from multiple sources or for multiple projects. For platforms needing continuous data access, credit limitations can create unplanned expenses or data gaps.
  2. Increasing Competitor Pressure: With many organizations relying on similar feature capabilities, the capabilities become commoditized between competitors. Increased competitor pressure, and churn, are often due to over-reliance on these commoditized capabilities.
  3. Loss of Engineering Product Focus: Talkwalker’s approach requires companies to handle their own data storage and management, which forces the technical teams of many organizations into considering and implementing “helper pipelines”. These efforts, which are not core to the offerings of the organizations, often cause spikes in engineering costs and delayed speed-to-market due to split focus.
  4. Need for Advanced Enrichment: As products mature, many require data enrichments beyond basic sentiment or topic identification. Companies that need granular sentiment analysis, detailed entity recognition, AI capabilities, or even custom enrichments may find Talkwalker’s offerings insufficient.
  5. Limited Historical Analysis: Talkwalker’s 30-day data window restricts long-term trend analysis, which is essential for companies needing to track patterns over months or years. If your platform is moving toward providing trend analytics, deeper insights, or historical comparisons, the API’s time limits could quickly become a constraint.

Migration: Paths for When Talkwalker no Longer Fits

For companies reaching the stage where Talkwalker’s API limitations are hindering product capabilities, the question becomes how to scale beyond it. Below are three common paths forward, from incremental shifts to full migrations.

  1. Hybrid Solution: Many companies take a gradual approach, retaining Talkwalker’s API for certain data sources while integrating a more flexible provider like Datastreamer for real-time or high-volume needs. Taking a “DIY” approach is a secondary option, but increases the need of “helper pipelines” which, if created and managed internally, can cause  “Pipeline Plateau” symptoms.
  2. Soft Upgrade: A phased approach allows companies to transition to a more advanced platform over time. By adding components from various parties into a Pipeline Orchestration Platform, companies can progressively migrate away from Talkwalker while minimizing disruptions and balancing resource requirements.

Full Upgrade: For mature platforms that have fully outgrown Talkwalker’s API limitations, a full upgrade to a new platform may be the best option. Moving entirely to a scalable, flexible Orchestration Platform like Datastreamer allows companies to bypass constraints such as rate limits and credit systems, while also gaining no-code abilities to add any enrichment, source, or capability required. This approach is ideal for companies needing a future-proof, high-powered data pipeline to support long-term growth.

Conclusion: Identify and Plan Migration before Product Stalling

Talkwalker provides a valuable entry point for companies launching social listening and media monitoring products, but its limitations often surface as companies scale and data needs evolve. From rate limits to export restrictions and limited enrichments, Talkwalker’s API can start to constrain the insights products that companies want to deliver.

In many cases, companies like Talkwalker use their own Pipeline Orchestration Platforms, and leveraging these underlying systems directly can be a massive benefit. 

Understanding limitations, identifying indicators, and beginning to plan and leverage migration is a critical step. It is important to avoid the “Pipeline Plateau” which may occur due to investing in-house capabilities in an effort to replicate Talkwalker capabilities. Leveraging a Data Orchestration Platform like Datastreamer is the correct decision to make.

The post When Will My Company Outgrow Talkwalker? A Guide for Social Listening Products appeared first on Datastreamer.

]]> Instagram APIs for Custom Monitoring | Official API v.s. Alternative API v.s. Scraping https://datastreamer.io/instagram-data-guide-official-vs-alternative-api-vs-scraping/ Wed, 09 Oct 2024 18:07:09 +0000 https://datastreamer.io/?p=40977 Instagram APIs for Custom Monitoring (Official vs Alternative APIs vs Scraping) By Juan Combariza October 2024 | 12 min. read Table of Contents Skip to Section Official Instagram API Alternative Instagram APIs (Third-Party) Instagram Scraping Instagram API for Social Listening Behind the brunch selfies and fashion haul posts, Instagram is ripe with rich information around […]

The post Instagram APIs for Custom Monitoring | Official API v.s. Alternative API v.s. Scraping appeared first on Datastreamer.

]]>

Instagram APIs for Custom Monitoring (Official vs Alternative APIs vs Scraping)

juan-combariza-picture

By Juan Combariza

October 2024 | 12 min. read

Table of Contents

Skip to Section

  1. Official Instagram API
  2. Alternative Instagram APIs (Third-Party)
  3. Instagram Scraping
Instagram APIs Graphics - Insights Architecture - Instagram API Alternatives

Instagram API for Social Listening

Behind the brunch selfies and fashion haul posts, Instagram is ripe with rich information around audience sentiment. Instagram is the fourth most visited website in the world, with an estimated 62.7% of users following or researching brands on the platform. Large organizations have kept a pulse on social conversations for years, but we’ve seen a surge in demand for insights teams (services or software platforms) to develop customized intelligence capabilities. This is made possible by hooking directly into an Instagram API, which facilitates access to raw Instagram data and allows for the manipulation of this data to craft customized intelligence outputs.

Instagram API’s are often used to feed custom reports, dashboards, or proprietary AI models:

  • Trend Prediction for Fashion: An insights platform might use predictive AI models that forecast upcoming fashion trends based on Instagram data. This enables their fashion brand customers to stay ahead of the curve by adapting their designs and inventory accordingly. 
  • Market Strategy Reports for Brands: A large marketing agency collaborates with a Fortune 500 brand to collect extensive online data, offering deeper insights than traditional focus groups. This comprehensive view reveals customer perception towards products & marketing campaigns.
  • Threat Intelligence Monitoring: A threat intelligence platform monitors online conversations on Instagram to detect potential threats to a company, individual, or corporation which could range from cyber threats to physical threats. 
juan-combariza-picture

Note from the author:

Our platform facilitates the integration of these APIs, so we’ve helped dozens of data product teams, outsourced dev. agencies, and in-house insights departments build pipelines to connect Instagram data into bespoke tools. I wrote this blog to outline the different data access methods available, assessing data capabilities and setup effort, with a focus on custom social media monitoring as the primary application.

Understanding Instagram Data Access

What is an Instagram API?

An Instagram API (Application Programming Interface) is a set of tools that allow developers to interact with the functionalities and data of Instagram. Think of it as a bridge between Instagram’s extensive database and your own applications. APIs can also be used as a way to enable functionalities in a product, such as automated scheduling. 

The focus of this blog is on the extraction of insights (instead of other API functionalities like post scheduling or account management).

Instagram API v.s. Social Listening Tools

Tools like Meltwater and Brandwatch allow brands to easily monitor Instagram conversations through pre-configured, code-free setups. In contrast, Instagram APIs present a low-code solution to integrate data feeds into custom tools. This approach offers granular customizability of data flows and the ability to implement deeper AI enrichments, differentiating your social listening solutions from existing players.

Instagram API Integration Methods & Costs

Source: Cost Savings Analysis of Pre-Built Pipeline Infrastructure

Data collection is only the first step in the supply chain of insights. You will still need a data pipeline infrastructure that will move and refine the raw information into clear intelligence.

Consider this simplified pipeline model:

sample-instagram-pipeline-skeleton

Option A: Build your own API infrastructure

While constructing REST API connectors from vendors into your systems seems straightforward, this approach often only addresses the initial and final stages of data handling (steps 1 and 6), potentially leaving gaps that impact the quality of insights you provide to your customers.

Option B: Pre-built pipeline platform

Pre-built pipeline components significantly cut down the time needed to add sophisticated data control into your social insights pipelines. Instead of individually maintaining 6-7 different API connectors (blogs feeds, news feeds, social feeds), you can consolidate them into 1 platform that enriches data utility and increases its strategic value.

Option 1: Official Instagram API

Instagram-API-data-fields
Overview: 

The official Instagram API, developed and maintained by Instagram itself, is crafted to offer regulated and structured access to the platform’s extensive data. This API is designed to ensure that third-party developers and businesses can interact with Instagram’s features and data in a way that upholds the platform’s strict data privacy rules and user protections.

Capabilities
  • User Profile Access: Basic information on profiles that you manage, including user IDs, usernames, bios, and profile pictures.
  • Post Metadata: Caption, media type, media URL, timestamp, hashtags and tagged users.
  • Engagement Metrics: Likes, comments, tagged users in comments, and shares for posts made by an account you manage.
  • Account Analytics: For business and creator accounts: Post performance (reach and performance), audience demographics, and other metrics you would see in the “insights” tab of your IG account.
  • Brand tags: You can retrieve posts where a brand or Business/Creator account is tagged (with an @), but this is restricted to content directly related to the accounts you manage.
  • Hashtag searches: The only form of public data search that is available through the Instagram Graph API is hashtag search.
  •  
Limitations
  • Restricted to accounts you manage: Does not support the search of content based on location, keywords, or entity mentions.
  • Only Identifies Direct Mentions: You will only be able to identify captions, comments, and media where an account has been directly tagged or @mentioned.
  • Lack of user profile data: With the Instagram Graph API, you do not have access to any user profile metadata for profiles that you do not manage or own
  • Rate Limits: The Instagram API enforces rate limits that cap the number of requests an application can make within a given time frame.
  • Historical search: The Instagram Graph API provides limited access to historical data, as it is primarily focused on insights and analytics for Business and Creator accounts

Instagram Graph API v.s. Basic Display API

Instagram Basic Display API: Restricted to personal accounts, this API doesn’t apply to Creator or Business profiles. It allows you to pull data solely from personal accounts that you’ve authenticated with login access. A typical scenario is using this API to display a personal Instagram feed on a website.

Instagram Graph API: The Graph API is designed for Instagram Business and Creator accounts. It is meant for businesses to retrieve data on posts, comments, and follower demographics for posts made by a business account you are managing.

Note: On September 4, 2024, Meta announced that the Instagram Basic Display API would become deprecated. You can retrieve data through the Instagram API with Instagram Login

Official Instagram API Pricing

There is no direct cost associated with accessing the Instagram Graph API itself, as it is provided by Facebook (Meta) for free. The actual use of the API can carry indirect costs, including the wages for developers and the overheads for server and pipeline infrastructure. Although it is free, using the Instagram Graph API does require approval from Instagram and comes with API rate limits that vary based on your access level.

Option 2: Instagram API Alternatives (Third-Party APIs)

Datastreamer - APIs for Instagram Data - Sample API Request
What is a third-party data collector?

Third-party APIs, or “unofficial APIs”, are often favored for social listening as they gather extensive public data (posts, comments, user profiles) with their own independent collection methods. This data can then be queried or integrated through API commands, allowing access to a wide array of metadata that the official Instagram API lacks.

Third Party APIs typically do not require you to set up any scraping, greatly reducing legal and compliance risks.

Building Custom Instagram Monitoring for Your Clients?

The quality of third-party APIs varies widely. There is no shortage of horror stories of poorly maintained API environments, low data quality, or an inability to stay up to date with changes in Instagram’s platform. Datastreamer is not a data provider, but we’ve worked with dozens of third-party APIs and streamline your integration process:

  • Tap into our pre vetted network of data providers
  • See custom data engineering components that differentiate
your insights from existing tools like Brandwatch
  • Test drive a pipeline to run pricing scenarios with real-world usage metrics
Datastreamer - Catalog Grid - Icon
We Build You a Free Pipeline
Third-Party API Data Fields

Available metadata changes based on which third-party API you are using. This list is based on the Instagram data partners we’ve worked with in the past:

  • Search Instagram Profiles: Profile name, profile URL, biography, links in bio, verified status, engagement metrics (followers, post count).
  • Search Instagram Posts: Media type, media URL, captions, hashtags, mentions, comments, engagement metrics (likes and shares), timestamps.
  • Monitor Real-Time Instagram Data: Access real-time data to gain proactive insights, such as establish alerts for customer service or assess real-time perceptions concerning entities.
  • Search Historical Instagram data: Depending on the vendor, access historical data that can span back several years. Feed this into trend or sentiment analysis that looks at conversation topics over time.
Capabilities (Social Listening)
  • Monitor Instagram Keywords & Phrases: Track specific keywords and phrases across social media posts and comments. For example, track “sustainable fashion” to analyze how often it’s discussed across social platforms and understand the sentiment around sustainable materials in the apparel industry.
  • Monitor Instagram Profiles: Keep tabs on the activity of specific user profiles, including updates, posts, and public interactions. For example, monitor the profile of influencer (@janedoe) to observe engagement trends and the effectiveness of her promotional posts for various brands.
  • Monitor Instagram Hashtags: Follow specific hashtags to capture all related content, providing insights into discussions around a specific topic. For example, follow the hashtag #TechInnovation2024 to gauge pre-event buzz and attendees expectations.
  • Monitor Instagram Brand Mentions: Automatically detect and analyze mentions of a brand across social media to understand audience perception. For example, set up alerts for any mentions of “Starbucks” to gather feedback on new product launches or store openings.
  • Monitor Instagram Mentions of Products, Places, People: Use Entity Recognition, an AI model with greater accuracy than keyword searches, to track mentions of products, places, or notable individuals to gather detailed insights into the perception and popularity of these subjects. For example, track mentions of “Tesla Model Y” across social media to collect user opinions and common issues.

Capabilities (Data Enhancement)

  • Customization in collection: Certain vendors permit collection customization requests, such as increasing the frequency of collection for a list of specific profiles.
  • Enrichments: Some third-party APIs include standard data enrichments like sentiment analysis and entity recognition. Advanced enrichments, like detecting action intent, enhancing location data, or translating languages, can be added by using a pipeline platform.
  • Multiple Platforms Supported: Many third-party APIs collect data from multiple social media platforms, providing broader coverage for a more complete analysis of social conversations.
  • Advanced filtering: With a pipeline platform, raw Instagram data feeds can be filtered and routed based on metadata conditions. For example, data streams can be distilled down to core elements (keywords/phrases), and then have all results translated into English.
Limitations
  • Data Interruptions: Since alternative APIs collect data as a third-party, a major Instagram platform update may disrupt collection while data aggregators adjust their tech to align with new changes.
  • Data Quality: Data integrity is dependent on the technology employed to collect it. Less sophisticated third-party APIs may only capture only a limited subset of the available data.
  • Developer Friendliness: Poorly built API environments can slow down speed-to-market speeds and create a recurring headache for developers tasked with maintaining integrations.
Are Third-Party Instagram APIs Legal?

Leveraging third-party APIs to access public data is generally legal and commonly utilized by large companies. Nonetheless, conducting proper due diligence remains important:

  • Understand compliance requirements with local privacy laws (GDPR or CCPA), as these regulations govern how personal data can be collected, stored, and processed. 
  • Ensure the intended use of the data and the handling of information within your pipeline align with legal and ethical guidelines.
Pricing for Instagram API Alternatives 
  • Usage based data consumption: Pricing often depends on the volume of data accessed via API calls. Prices are tied to the scope of data queries, such as hashtag searches, profile analysis, and the choice between historical or real-time data access.
  • Pipeline infrastructure costs: There are costs associated with the underlying infrastructure required to support the data pipeline. This includes servers, data storage, and the network resources needed to process and handle the data streams efficiently.
  • Integration setup & maintenance:  Labor costs are involved in both the development of API connectors and their ongoing maintenance to ensure stable connections to diverse data sources
Running a Pilot Pipeline To Forecast Costs

Estimating the exact costs of using third-party Instagram APIs can be complex due to the variability in data usage and API call frequency. Since insights teams rarely know their exact data usage ahead of time, the most effective method to predict expenses is by conducting a pilot test.

Running a scaled-down version of the intended data pipeline allows teams to gather actual usage statistics, providing a realistic basis for cost projections

Option 3: Instagram Scraping

What is Instagram Scraping?

Instagram scraping is a method where data is programmatically extracted directly from the web pages of Instagram. This technique involves writing scripts or using software that simulates the actions of a web browser to gather visible data from the platform’s frontend. While scraping can provide access to a wide range of data that might not be available through official channels, it requires a solid understanding of both programming and the legal implications involved.

Capabilities
  • Comprehensive Data Extraction: Scrapers can be tailored to collect detailed information from Instagram, such as user comments, post timings, and hashtag usage, which are visible on public profiles and pages.
  • High Customizability: Since scraping scripts are custom-built, they can be designed to meet specific data requirements, targeting exactly what is needed without redundancy.
Limitations
  • Fragility of Setup: Instagram frequently updates its site layout and underlying code, which can render scrapers obsolete overnight. This requires constant maintenance of scraping scripts to ensure they remain effective.
  • Legal and Compliance Risks: Scraping data from Instagram can breach the terms of service set out by the platform, potentially leading to legal actions or bans from the site. Moreover, data privacy regulations like GDPR and CCPA impose additional layers of compliance, which scraping might violate.
  • Data Integrity Issues: Data collected via scraping is only as good as the scraper’s design and the public visibility of data. Automated scrapers may not always interpret page layouts and data formats consistently, particularly if Instagram changes its interface.
Costs
  • Initial Setup Costs: While starting costs for scraping can be minimal—especially if using open-source tools or low-code tools—the real investment is in the development of robust scraping scripts.
  • Maintenance Expenses: Ongoing costs can escalate due to the need for regular updates and troubleshooting of scraping scripts to keep up with changes on Instagram’s platform.
  • Infrastructure Costs: Establishing custom scrapers addresses the initial data collection needs, but a real-time data pipeline to power an insights solution involves additional infrastructure. This adds overhead costs for data handling, processing, and storage.
Strategic Considerations

While scraping might seem like a low-cost solution for accessing extensive data from Instagram, it comes with significant operational and legal risks that can affect its overall viability and sustainability. Businesses considering this approach must carefully evaluate their capability to manage these risks and the potential impact on their operations and reputation.

The post Instagram APIs for Custom Monitoring | Official API v.s. Alternative API v.s. Scraping appeared first on Datastreamer.

]]> 5 Best Review APIs | No Scraping Required to Integrate Review Data Feeds https://datastreamer.io/5-best-review-apis-no-scraping-required-to-integrate-review-data-feeds/ Mon, 22 Jul 2024 01:12:53 +0000 https://datastreamer.io/?p=40529 The 5 Best Review APIs | Integrate Online Reviews Data Into Custom AI Models Juan Combariza May 2024 | 8 min. read Table of Contents Top Picks Datastreamer: Best for Insights teams Socialgist: Best for English & Chinese Review Platforms Reviewapi.com: Best for small-scale projects Real-Time Reviews Data for Your Apps & Reports The Shift […]

The post 5 Best Review APIs | No Scraping Required to Integrate Review Data Feeds appeared first on Datastreamer.

]]>

The 5 Best Review APIs | Integrate Online Reviews Data Into Custom AI Models

juan-combariza-picture

Juan Combariza

May 2024 | 8 min. read

Blog Header - Reviews APIs

Table of Contents

Top Picks

  1. Datastreamer: Best for Insights teams
  2. Socialgist: Best for English & Chinese Review Platforms
  3. Reviewapi.com: Best for small-scale projects

Real-Time Reviews Data for Your Apps & Reports

The Shift Towards Customized Review Monitoring Feeds

Behind Twitter and Instagram, social listening professionals ranked Reviews and Forums data as the most important sources for insights in their organization. Twitter (X) & IG have widespread availability in nearly every social listening tool, while harnessing reviews data requires more customized collection and some additional steps in procurement. Still, 75% of intelligence professionals surveyed said reviews are an important source for their insights preparation.

Customized reviews APIs help businesses access customer feedback from sources like Google, TripAdvisor, or eCommerce platforms in a targeted manner. This includes features like filtering and refining reviews data and focusing on specific keywords (locations, products, and competitors).

Why Data Teams Prefer APIs over No-Code UIs

For pulling data from review sites, visual tools can be useful for simple keyword-based queries. However, when the integration demands the application of NLP techniques or specific data stream customization, APIs become essential. These tools are more complex but offer greater control, granting data professionals the flexibility to innovate in their analysis methods. Review data, in particular, often needs more targeted collection methods than other types of data. 

APIs allow you customize data flows that suit your existing infrastructure:

  • Trend Forecasting with Custom AI: A trend prediction platform working with fashion retailers deploys review monitoring APIs to gather and analyze customer feedback from major e-commerce platforms like Amazon Fashion. The collected data is enriched with sentiment and a transformed metadata structure through the API. Then it is combined with predictive AI created in-house to deliver a nuanced understanding of market shifts and emerging fashion trends. These insights allow clients to proactively adjust their inventory and marketing strategies, ensuring they capitalize on trends as they emerge.
  • In-House Social Listening (Brand Reputation): An in-house social listening team can set up a review monitoring API to track mentions and sentiments about their brand across multiple review sites such as Google Reviews and TripAdvisor. This is crucial for maintaining a positive brand image and quickly addressing any negative feedback or crises before they escalate. With an API, data can be blended with customer survey responses to cross-examine and draw holistic insights. 
  • Marketing Insights Reports: An agency working with multinational food brands prepares detailed insight reports by utilizing review monitoring APIs. These reports aggregate vast amounts of customer feedback, synthesizing it into actionable intelligence on consumer satisfaction trends and changing preferences. These insights are delivered to stakeholders to inform strategic planning and ensure alignment in new product development.

Review Scraping Tools v.s. Reviews APIs

Review Scraping Tools: Solutions like Brightdata help you set up your own scraping of review sites. You’ll have to set up proxies and custom coding elements to handle pagination and data extraction. Although these tools reduce the complexity compared to building from the ground up, they still require manual effort.

  • Pros: Custom scraping offers the capability to collect the exact data you want from virtually any website.
  • Cons: Legal issues, difficult to scale, and each website scraped will require bespoke configurations.

Typically, review scraping tools are recommended for small-volume projects or for collecting niche data that isn’t available through standard Review APIs.

First-Party Reviews APIs: This term refers to an API provided directly by the primary source or owner of the data. For example, you can access an API that is offered and maintained by Yelp or TripAdvisor directly.

  • Pros: Utilizing official APIs minimizes the risk of breaching a website’s usage policies. Data quality – Direct access to a platform’s database may include metadata not available through third-party APIs.
  • Cons: First-party APIs offer data exclusively from their own platforms, a scope that rarely meets the broader data collection goals of intelligence teams. As a result, organizations must establish and maintain infrastructures for several different API connectors, increasing overall costs.

Third-Party Reviews APIs: These solutions collect and aggregate data from multiple review platforms into a single data stream. This is often achieved with partnerships with first-party APIs and scraping from additional platforms, but it demands no scraping effort from the end-user, who only needs to configure their queries.

  • Pros: Data coverage spans multiple platforms and is delivered in a structured format that is ready for analysis.
  • Cons: Third-party APIs may be more expensive than any individual first-party alternatives, but these costs level out if you want to leverage multiple sources.
juan-combariza-picture

Note from the author:

The solutions listed in this blog primarily focus on Third-party APIs. We usually recommend these to our customers because they cover a broad range of review platforms, include options for customized data collection, and don’t require any scraping by the end-user (lowering compliance concerns).

List of Review APIs to Integrate into Your Tools

1. Datastreamer – Best for Insights Teams

Datastreamer - API for Real-Time Reviews - Example Query (4)
Simplified query for illustrative purposes

While review aggregators provide simple API access to customer feedback, the real challenge lies in the need to create and maintain extra infrastructure to process this data and implement sophisticated AI models. Considering that intelligence teams usually work with 6+ third-party APIs; and technical setup consumes 5-7 weeks per source, you end up with months of roadmap time dedicated to procurement and integration. Our comparative analysis highlights how a pipeline platform, which offers pre-built infrastructure, cuts down implementation time by 720+ hours per source and increases the utility of the data collected.

Review Data Coverage Details

Datastreamer does not collect review data, but as a pipeline platform, we have integrated partners who provide review content. Access these feeds via an API query, just like you would when working directly with a third-party API:

  • Reviews from 250+ platforms (such as TripAdvisor)
  • Data from Chinese Reviews platforms
  • eCommerce review data feeds
  • Upon request, new review sites that are not already collected can be added. 

You can connect any third-party API to Datastreamer, enabling you to leverage our advanced analysis models and orchestration components with your existing feeds.

Why Use A Pipeline Platform Over Individual APIs

One API Query to Access News Feeds from Multiple Vendors 

Merging online feeds from various data providers into a single API platform significantly lightens the workload for your developers and analysts. 

  • Additional data feeds include social media, forums, blogs, news and more. 

Add New Data Value with Plug & Play Engineering Components

Human generated content will inevitably come with irrelevant noise. This can be drastically reduced with NLP models that are trained to pick up on contextual nuances to reduce false positives. 

  • Instantly deploy NLP models such as location inference or entity recognition on multiple languages.
  • Activate “traffic control” elements like JSON metadata filters and conditional routing.
  • Harness enterprise-level data management with visual pipeline tracking and debugging options.

Datastreamer Pricing for Reviews APIs

Pricing for data feeds is set by our partners, and are typically the same as if you work directly with their third-party API. We do not markup prices on data feeds. You pay Datastreamer for the pipeline components (enrichments, data orchestration, transformations) that you use to process your data.

Pricing

  • Pricing is based on usage, with a minimum spend of $150/month.
  • Our team can facilitate a quote based on usage estimates and desired data sources.

Free Trial

  • Datastreamer will build you a pipeline with Review data, that you can run free for 14 days.
  • A product manager helps you demo the pipeline to stakeholders and configure components.

2. Socialgist

Socialgist-review-api-image

Socialgist is a top choice as a reviews data API, and this platform focuses primarily on social media and online discussions. 

Socialgist gathers comprehensive reviews data (including user comments) from a variety of platforms. The platform also lets you access historical data, making it ideal for forecasting consumer trends and conducting market research. Socialgist is a good option for businesses seeking insights based on brand engagement, sentiment analysis, and market intelligence.

Socialgist Review Sites Available

  • Socialgist collects reviews from over 250 English review platforms. Sites collected have a focus on consumer products and travel, such as TripAdvisor.
  • Socialgist also offers data from 50+ Chinese review sites.

Can I request an additional review site to be collected by Socialgist? Yes, you can ask Socialgist to include any review sites they aren’t already tracking by requesting them to index the additional site.

Socialgist Review Sites Coverage Details

Update FrequencyHistorical LengthLanguagesOutput Format

Hourly, Daily, or Real-Time

2 Years

English, Chinese

Structured JSON

Pricing

  • Pricing is not publicly displayed. You can reach out to get a pricing quote over email.

Free Trial

  • A free trial is not publicly advertised by Socialgist, but you can reach out to inquire.

3. Review API.com

Review API might look like a more minimal-featured entrant on this list. However, this platform specializes in gathering reviews from customer and consumer-based sites like Amazon, Facebook, Sitejabber, Healthgrades, and Aliexpress. 

This review monitoring API gathers reviews and other data from multiple platforms with use cases like feedback applicable to marketplaces, customer success management, brand monitoring, and machine learning. Review API offers free tools as well as flexible pricing plans, from small to medium and large to very large.

Review API Review Sites Scraped

This review scraper gathers data from over 30 sources like Amazon, AliExpress, Trustpilot, Yelp, and Tripadvisor.

Can I request an additional review site to be collected by Reviewapi? This feature is currently not available on Review API. However, custom large pricing plans include personalized support which could be leveraged for additional review sites.

Reviewapi Review Sites Coverage Details

Update FrequencyHistorical LengthLanguagesOutput Format
On-demand

N/A

EnglishStructured JSON

Pricing

  • Pricing starts at $79/month with limited features.
  • High-end plans of $399/month and $750/month include all features.

Free Trial

  • You can try the free version with a limited 1000 API credits and 30 reviews per review job.

4. Brightlocal

brightlocal-review-api-image

Brightlocal’s Monitor Reviews is among the top APIs for review site data. The platform specializes in helping organizations advance their marketing goals, particularly local marketing. From boosting rankings to reputation management, the platform has helped over 80,000 local marketers ace their customer success and brand health goals.

Brightlocal’s Monitor Reviews tool tracks reviews across industries like automotive, medical, legal, real estate, home services, wellness, FnB, and mechanics.

Brightlocal Review Sites Scraped

Brightlocal tracks over 80+ general and niche review sites like Yellow Pages, Facebook, Tripadvisor, Yelp, Google, and Foursquare.

Can I request an additional review site to be collected by Brightlocal? We were unable to locate any information regarding this query on BrightLocal’s website or their support materials.

Brightlocal Review Sites Coverage Details

Update FrequencyHistorical LengthLanguagesOutput Format

Daily Reports

N/A

English

JSON

Socialgist – Natively Provided Enrichments

  • Entity extraction (people, products, brands, companies), Topic categorization (custom taxonomies), Sentiment analysis, Demographic information (age, gender, location), Trend analysis, Clustering by topic

Pricing

  • You can monitor reviews with the ‘Grow’ plan of $59/month.

Free Trial

  • All three paid plans have a 14-day free trial period you can access without a card.

5. Webz Reviews API

Webz is among the top review sites scraper platforms excelling at collecting and organizing big data into actionable insights. With native enrichments like archive search functionality and smart extraction (who, what, where, when), Webz is ideal for media monitoring and sentiment analysis.

The platform’s Reviews API lets you access structured customer feedback and monitor product health and visibility with real-time news data feed features. Webz boasts of 600M+ reviews collected and 900+ eCommerce sites and marketplace tracked, making this platform a great tool to track customer and product insights.

Webz Review Sites Scraped

Webz gathers ecommerce review data from 950+ sites. They do not mention how many non-ecommerce sites they collect data from.

Can I request an additional review site to be collected by Webz? Yes, you can request for additional review sites and sources to be added and explore custom data.

Webz Review Sites Coverage Details

Update FrequencyHistorical LengthLanguagesOutput Format

Real-time (on-demand)

10+ years

English and others

JSON or XML

Pricing

  • Pricing is not publicly available. 
  • You can request a quote for custom pricing based on requirements.

Free Trial

  • You can schedule a demo or sign up for a free trial.

The post 5 Best Review APIs | No Scraping Required to Integrate Review Data Feeds appeared first on Datastreamer.

]]> How to Integrate a News Data API | 2 Alternatives to DIY Scraping https://datastreamer.io/how-to-integrate-a-news-data-api-2-alternatives-to-diy-scraping/ Mon, 08 Jul 2024 02:45:58 +0000 https://datastreamer.io/?p=40373 How to Integrate a News Data API | 2 Alternatives to DIY Scraping Juan Combariza July 2024 | 8 min. read Table of Contents Alternatives to DIY News Scraping Scraping news data DIY is fraught with challenges. Technically, it demands setting up and managing proxies, handling IP bans, and parsing HTML from different structures—tasks requiring […]

The post How to Integrate a News Data API | 2 Alternatives to DIY Scraping appeared first on Datastreamer.

]]>

How to Integrate a News Data API | 2 Alternatives to DIY Scraping

juan-combariza-picture

Juan Combariza

July 2024 | 8 min. read

Header - How to Integrate a News API (1)

Table of Contents

Alternatives to DIY News Scraping

Scraping news data DIY is fraught with challenges. Technically, it demands setting up and managing proxies, handling IP bans, and parsing HTML from different structures—tasks requiring substantial coding expertise and resources. Opting for established news data APIs or a pipeline platform eliminates these hurdles, offering a reliable, efficient, and legally compliant way to access rich news data.

Step by Step Guide to Integrating News Data API

1. Procurement – Finding a News Data Collector

Method A – Manually Procuring a Data Vendor: Begin by identifying and evaluating potential data vendors. Look for providers that offer comprehensive global news coverage, ensuring you receive a wide array of viewpoints and news events. Assess the vendor’s reliability, update frequency, historical data access, and the types of enrichments they offer. Legal compliance and the vendor’s ability to provide support should also be major considerations.

  • 💡 To save time on research, you can check out our list of Top News Data APIs where we have already assessed these criteria for the industry leading vendors.

Method B – Using a Pre-Vetted Partner Catalog: Datastreamer simplifies this by providing a pre-vetted, comprehensive catalog where you can test and select different news data providers.

2. Pipelines – Connecting Vendor APIs to Your Systems

Method A – API Connection Directly to Data Vendor: This process typically requires detailed technical planning. Your IT team must set up and maintain API connections, manage data formatting and normalization, and ensure that the data flow remains uninterrupted.

A typical process flow for a DIY pipeline includes Python scripts to handle API calls, event hub processing systems like Apache Kafka, which can handle high throughput and enable real-time data streaming, and data pipeline tools such as Microsoft Azure Data Factory ato orchestrate and automate the data flow. This setup requires ongoing maintenance to adapt to API changes and manage data integrity.

Process Flow for In-House Pipelines

  1. API Setup

    • Authentication: Implement OAuth or API key-based authentication to securely connect to the news data API.
    • Python Scripting: Write Python scripts to handle API requests and responses. Use libraries such as requests or aiohttp for making HTTP calls.

  2. Data Retrieval

    • Scheduled Polling: Set up scheduled tasks (using cron jobs or Python’s schedule library) to periodically make API calls.
    • Real-Time Streaming: If supported by the API, implement a streaming connection using WebSockets or long polling to receive data as it becomes available.

  3. Data Processing

    • Event Hub Processing: Utilize Apache Kafka to manage high-throughput, real-time data streams, ensuring robust handling of incoming data.
    • Data Filtering and Transformation: Use Apache NiFi or custom Python scripts to filter irrelevant data and transform data into the desired format.

  4. Data Integration

    • Pipeline Orchestration: Implement Apache NiFi for orchestrating data flow from the API to the internal systems, providing capabilities for routing, transformation, and system mediation.
    • Data Storage: Store raw data in temporary storage for further processing or move directly to a permanent data store such as a database or data warehouse.

  5. Data Enrichment

    • Apply Enrichments: Enhance data with additional context or metadata using Python scripts for sentiment analysis, named entity recognition, etc., often leveraging machine learning models or external libraries.
    • Integration of Custom Enrichments: If specific business rules or custom analyses are needed, integrate these using additional Python scripts or third-party services.

  6. Data Delivery

    • APIs for Internal Consumption: Develop internal RESTful APIs using frameworks like Flask or Django to serve processed and enriched news data to other internal applications.
    • Direct Database Integration: Use SQL or NoSQL databases to store processed data, ensuring that it is accessible for analysis and reporting.

  7. Maintenance and Monitoring

    • Logging and Error Handling: Implement comprehensive logging for all stages of the pipeline. Use monitoring tools like Prometheus or Grafana to track the health and performance of the pipeline.
    • Regular Updates: Regularly update API integration scripts and libraries to accommodate changes in the news data API and to patch security vulnerabilities.

  8. Compliance and Security

    • Data Compliance: Ensure that all data handling practices comply with relevant legal and regulatory requirements, particularly concerning data privacy.
    • Security Measures: Implement security measures such as HTTPS for data transmission, encryption for stored data, and secure authentication mechanisms.

Method B – Pipeline Platform: Datastreamer simplifies the integration process dramatically. Its pre-configured connectors and robust infrastructure facilitate swift integration with your current systems.

Datastreamer consolidates functions like API calls, event processing, data transformation, and orchestration into a unified platform, equipped with a visual builder designed specifically for managing data streams from external APIs like news data providers.

3. Enriching the Data

Method A – DIY API Connection: When directly connecting to a data vendor’s API, you often get basic data enrichments like sentiment analysis or entity recognition. However, if your use case requires advanced enrichments (contextual NLP models, or predictive analytics), you’ll need to incorporate additional tools or infrastructure which can be resource-intensive.

Method B – Pipeline Platform: Datastreamer offers a range of built-in advanced data enrichments. These include sophisticated NLP models (such as ESG, location inference, and intent) that reduce noise by focusing on relevant data points. These enrichments can be applied instantly, ensuring that the data you integrate is immediately more actionable and insightful.

4. Using Data for Insights or Visualization

Method A – DIY API Connection: After setting up the API, the data delivered needs to be ingested into your systems. Depending on the vendor, you might receive data through RESTful APIs, HTTPS requests, or streaming interfaces. Each method may require different handling in your system, possibly necessitating additional programming work to convert and format the data as per your analytical tools’ requirements.

Method B – Pipeline Platform: With Datastreamer, the process is streamlined as the platform includes pre-built connectors that deliver data in formats compatible with major data warehouses and analytical tools such as Databricks or Snowflake. The platform also supports storing data in a high-speed searchable format, allowing for custom integration into your product’s analytical environment, optimizing readiness for analysis and visualization.

(Optional Step) Testing with a Free Trial/Demo

Before committing resources, it’s advisable to test the integration through a free trial or demo. This allows your team to assess the quality of the data, the ease of integration, and the relevance of the data enrichments provided. Trials also help in determining the responsiveness of the vendor’s support team and the overall reliability of the data feed.

We'll Build You a Free News Data Pipeline

Test drive a pipeline, free for 14 days. We’ll set it up with live data and use it to determine real-world cost estimates and the time savings delivered for your engineering team.

Get A Free Pipeline

How Businesses Use News Data APIs

Businesses across various sectors increasingly rely on integrating news data feeds to enhance their decision-making processes. For instance, in Threat Intelligence, real-time news can pinpoint emerging risks, from cyber threats to geopolitical unrest. Consumer Insights and Trend Prediction leverage news to gauge market sentiments and predict shifts in consumer behavior. In-House Social Listening platforms utilize news data to monitor brand mentions and customer feedback across multiple channels. Additional use cases like competitive analysis and regulatory compliance further illustrate the indispensable value of integrated news data in creating detailed reports, dynamic visualizations, or immediate alerts for end-users.

The post How to Integrate a News Data API | 2 Alternatives to DIY Scraping appeared first on Datastreamer.

]]>