Automatic Pricing (by Dataria) vs. PriceLabs: 哪个更适合您?

更新于 May 16, 2026  ·  已分析 51 条经验证的评价

摘要

我们分析了 51 条经验证的酒店从业者评价,比较了功能集、定价和真实案例研究,以全面解析每个平台的优势。最佳选择取决于您的物业类型和优先事项:

Dataria 表现出色 ,拥有独特功能如 "What-if" scenario analysis and Manage Sell-Outs & Cancellations.

PriceLabs 表现出色 在 动态定价和收益管理 方面 ,拥有独特功能如 Alternate Stay Date Recommendations and Event Data.

查看下方完整分析 ↓

Automatic Pricing (by Dataria) 与 PriceLabs 相比如何?

基于 HTR 上 51 条经验证的酒店从业者评价的并排评分。

HTScore
0
75
推荐可能性
100%
100%
易用性
4.7/5
4.8/5
客户支持
5.0/5
5.0/5
性价比
4.8/5
4.9/5
起始价格 From $400/mo From $600/mo
经验证的评价 6 45

Automatic Pricing (by Dataria) 与 PriceLabs 的优缺点是什么?

在分析了 51 条经验证的评价后,Dataria 用户最看重其 ,而 PriceLabs 用户则强调 动态定价和收益管理, 技术支持和响应能力, 市场比较与情报。点击任意主题查看评价者的反馈。

Dataria Dataria PriceLabs PriceLabs
优点
+ 动态定价和收益管理
+ 技术支持和响应能力
+ 市场比较与情报
+ 定制和灵活性
缺点
改进空间:附加功能

Dataria 对比 PriceLabs:按酒店细分市场排名

各产品在不同物业规模、类型和区域的 收益管理系统 供应商中的排名——基于各细分市场中酒店从业者的经验证评价。

按酒店规模

细分市场 Dataria Dataria PriceLabs PriceLabs
小型(10-24 间客房) #34 2 条评价 #21 14 条评价
中型(25-74 间客房) #43 2 条评价 #23 11 条评价
大型(75-199 间客房) #15 5 条评价
超大型(200+ 间客房) #12 4 条评价

按物业类型

细分市场 Dataria Dataria PriceLabs PriceLabs
精品酒店 #43 1 条评价 #27 15 条评价
豪华酒店 #22 13 条评价
品牌/连锁酒店 #43 1 条评价 #25 6 条评价
长住酒店 #12 7 条评价

按区域

细分市场 Dataria Dataria PriceLabs PriceLabs
北美 #26 1 条评价 #12 21 条评价
欧洲 #30 3 条评价 #21 12 条评价
亚太 #11 4 条评价
中东 #14 2 条评价

The Decision

Your hotel needs an effective revenue management system to optimize room rates, maximize revenue, and stay competitive. Both Automatic Pricing (by Dataria) and PriceLabs Dynamic Pricing aim to automate and enhance your pricing strategy, but they differ significantly in features, user experience, and market presence. Which system aligns better with your hotel’s specific needs and operational goals?

While PriceLabs has garnered more recent reviews and a larger user base, Dataria’s deep feature set and niche focus might still appeal to certain operators. What should you prioritize — breadth of features or recent user feedback?

Is Automatic Pricing (by Dataria) or PriceLabs Better for Hotels?

Both systems strive to automate hotel pricing, but their core approaches and market focus diverge. Dataria emphasizes precise, tailored algorithms combined with extensive data insights like competitor prices, demand, and occupancy, aiming to maximize revenue without sacrificing control. PriceLabs, on the other hand, offers a user-friendly interface with real-time market comparisons and extensive automation, suited for those who want a flexible, easy-to-manage solution.

Dataria’s limited review count (only four reviews, none in the last six months) makes its current data less reliable for decision-making. PriceLabs, with 44 reviews and more recent feedback, provides a clearer picture of user satisfaction and platform performance today. Are you comfortable with a smaller, less recent dataset, or do recent user experiences matter more?

PriceLabs vs Automatic Pricing: Which Should Your Hotel Choose?

If your hotel operates a large portfolio, especially in vacation rentals, or values robust market comparison features, PriceLabs is the logical choice. Its extensive integrations, higher review volume, and recent positive feedback indicate a more mature, widely adopted platform.

Conversely, if your hotel is a boutique or city-center property seeking a tailored, algorithm-driven approach with a focus on detailed analytics and forecasting, Dataria’s niche features like scenario analysis and five-year forecasting could be advantageous. However, the limited recent reviews and smaller user base make PriceLabs a safer bet for most hoteliers.

Is Automatic Pricing (by Dataria) or PriceLabs Easier to Use?

PriceLabs scores slightly higher in ease of use at 4.77/5, with most reviews praising its intuitive interface and responsive support team. Users highlight how straightforward it is to adjust rates, visualize market data, and manage multiple properties.

Dataria’s ease of use is rated 4.5/5, with reviews emphasizing its intuitive platform but noting a need for more comprehensive documentation to speed onboarding for new team members. The smaller support team and fewer recent reviews reduce confidence in current usability.

Edge: PriceLabs.

Which Has Better Features: Automatic Pricing (by Dataria) or PriceLabs?

Dataria offers 13 unique features, including “What-if” scenario analysis, group pricing, multi-factor authentication, and a five-year forecast builder—capabilities that appeal to data-driven, strategic users. PriceLabs provides only 3 exclusive features, such as event data, alternate stay recommendations, and STR data, but covers the essentials well.

PriceLabs’s focus on core dynamic pricing, market comparison, and multi-unit management makes it suitable for most hotels, while Dataria’s specialized tools cater to hotels seeking deep analytical control. Given the feature counts, edge: Dataria.

Which Has Better Customer Support: Automatic Pricing (by Dataria) or PriceLabs?

Dataria’s support scores a perfect 5/5, with reviewers emphasizing its personalized, unhurried onboarding and ongoing support. One review cites, “The Dataria team is always available, understands the hotel business, and truly supports you,” demonstrating a high level of customer care.

PriceLabs support is rated at 4.98/5, with reviews praising responsiveness, though some note room for faster resolution times. Overall, both platforms excel, but Dataria’s smaller support team and dedicated onboarding give it the edge.

Edge: Dataria.

Which Has More Integrations: Automatic Pricing (by Dataria) or PriceLabs?

PriceLabs boasts 34 verified integrations, including major PMS and channel manager partners like Cloudbeds, RMS, and Kigo, making it highly adaptable in diverse tech stacks. Dataria’s 3 verified partners include Mews, Neobookings, and their own platform, limiting integration options.

For hotels with complex, multi-platform operations, PriceLabs’s broader integration network offers greater flexibility. Edge: PriceLabs.

Which Do Hoteliers Rate Higher: Automatic Pricing (by Dataria) or PriceLabs?

PriceLabs’s reviews are significantly more recent and plentiful, with 42 reviews and a 4.77/5 ease of use score, indicating high satisfaction among a broad hotel segment including vacation rentals, boutique hotels, and larger properties.

Dataria’s four reviews, all older and with a perfect 5/5 score, suggest positive sentiment but lack recent data to confirm continued performance. Given current review volume and recency, edge: PriceLabs.

How Much Do Automatic Pricing (by Dataria) and PriceLabs Cost?

Dataria charges $400 per month for their service, with no free trial or implementation fees. PriceLabs costs $600 per month and offers a 30-day trial, providing a risk-free period to evaluate the platform.

While PriceLabs is more expensive, its larger feature set, integrations, and recent positive reviews may justify the premium for many hoteliers.

What Type of Hotel Should Use Automatic Pricing (by Dataria)?

  • Hotels that need deep, customizable data analytics, including forecasting, scenario analysis, and detailed competitor insights.
  • Hotels that prioritize tailored pricing policies based on occupancy, demand, and internal data.
  • Teams comfortable with a smaller, niche provider willing to invest in personalized support.
  • Hotels that prefer a platform with advanced forecasting and multi-factor analytics.

Not ideal if:

  • You require extensive integrations with third-party systems.
  • You operate a large, multi-location portfolio needing broad automation.
  • You prefer a platform with a more extensive, recent user base.

What Type of Hotel Should Use PriceLabs Dynamic Pricing?

  • Hotels managing multiple properties or large portfolios, especially in vacation rentals or extended stay segments.
  • Hotels seeking a responsive, easy-to-use platform with extensive integrations.
  • Teams that value market comparison features, real-time adjustments, and extensive automation.
  • Hotels looking for a cost-effective, popular solution with a strong track record of recent reviews.

Not ideal if:

  • You need highly specialized analytics or scenario planning.
  • You operate a small boutique hotel that prefers tailored, manual control.
  • Your focus is on niche features like multi-year forecasting or detailed internal analytics.

The Bottom Line for Hotels

Dataria’s Automatic Pricing offers advanced, tailored analytics, ideal for hotels with complex data needs and a desire for customizable strategies. Its small but dedicated support team and niche feature set make it suited for properties seeking deep control and forecasting.

PriceLabs excels in ease of use, integration breadth, and recent reviews, making it a more reliable choice for hotels needing scalable, real-time pricing adjustments across multiple properties. Its extensive market comparison and automation capabilities benefit operators aiming to maximize revenue with minimal manual effort.

If your hotel prioritizes recent user feedback, ease of deployment, and broad integrations, PriceLabs is the clear winner. For those with specialized analytical needs and a smaller operation, Dataria remains a solid, albeit less-reviewed, option.

Ultimately, for most hotels today, the better choice is PriceLabs, given its larger user base, recent positive feedback, and extensive feature set. However, if your hotel values deep data control and forecasting, and you’re comfortable with a smaller, niche platform, Dataria remains worth considering.

Automatic Pricing (by Dataria) 和 PriceLabs 的价格是多少?

收益管理系统 的定价很少是简单明了的。以下是我们从各供应商公开定价数据中了解到的信息。请务必根据您的物业规模申请定制报价。

Dataria Dataria PriceLabs PriceLabs
Starting Price From $400/mo From $600/mo

Automatic Pricing (by Dataria) 有哪些 PriceLabs 没有的功能(反之亦然)?

根据 HTR 的产品数据库,Automatic Pricing (by Dataria) 和 PriceLabs 共享 40 项功能。以下是关键差异——一方拥有而另一方缺少的功能。

功能 Dataria Dataria PriceLabs PriceLabs
STR 数据
“假设”情景分析
丢失的业务数据
事件数据
可定制的通知和警报
团体定价与评估
备用住宿日期建议
管理售罄和取消
财务预测生成器

显示主要差异。这两款产品之间还有 4 项功能存在差异。

实际成果:Dataria 对比 PriceLabs(按业务目标)

我们分析了 4 个经验证的案例研究,比较了酒店在四个关键业务目标上使用每个平台实际取得的成果。

增加收入和降低成本
Dataria Dataria

该目标暂无已发布的案例研究。

PriceLabs The Neighborhood Hotel 大型
+ Increased Occupancy: By adjusting minimum stay requirements and leveraging dynamic pricing, they filled more rooms without drastically lowering rates.
+ Optimized ADR: Despite increasing occupancy, they maintained a healthy ADR by attracting the right mix of guests and avoiding over-discounting during low seasons.
+ Improved Operational Efficiency: Automation reduced the time spent on manual pricing adjustments, allowing Matthew to focus on strategic initiatives.

"The hotel in Lincoln Park is over 75% occupied in 2024 with a RevPAR $219.91. The one in Little Italy hotel is over 72% occupied in 2024 – our first year operating the hotel. Both..."

Matthew Shanley
Matthew Shanley
Director of Revenue Management and Opera...
提高运营效率
Dataria Dataria

该目标暂无已发布的案例研究。

PriceLabs Federica Mantovani 中型
+ Achieved a 20% to 25% increase in revenue for her boutique hotel using PriceLabs.
+ Significantly reduced the time and effort required for revenue management by automating pricing adjustments.
+ Successfully transitioned into a revenue management consultant, helping other hotels improve their revenue strategies.

"If you’re a beginner, you can set up the account in just a few hours by attending training webinars or looking at articles. On the other hand, if you are an experienced revenue man..."

Federica Mantovani
Federica Mantovani
Owner of The Coo’s Guest House

Dataria 对比 PriceLabs:总结

Dataria
Dataria
5.0/5 来自 6 条评价

排名更高的方面

ES #10 vs #14

独特功能

“假设”情景分析 管理售罄和取消 财务预测生成器 团体定价与评估 丢失的业务数据
4.7/5 易用性 5.0/5 客户支持 3 个集成
查看资料
PriceLabs
PriceLabs
5.0/5 来自 45 条评价

酒店从业者喜爱的方面

动态定价和收益管理 100% 正面

用户高度赞赏 PriceLabs 的动态定价模型,该模型可根据需求、季节性和市场趋势调整价格。此功能有助于在高需求期间获得价格溢价,并在低需求期间优化入住率,从... 用户高度赞赏 PriceLabs 的动态定价模型,该模型可根据需求、季节性和市场趋势调整价格。此功能有助于在高需求期间获得价格溢价,并在低需求期间优化入住率,从而实现收入最大化。

技术支持和响应能力 95% 正面

虽然关于客户支持的总体反馈是积极的,但一些用户认为技术支持可以更积极主动。注意到功能冻结和批量操作缓慢的问题,以及增强集成支持和更频繁的教育资源的建议... 虽然关于客户支持的总体反馈是积极的,但一些用户认为技术支持可以更积极主动。注意到功能冻结和批量操作缓慢的问题,以及增强集成支持和更频繁的教育资源的建议。

市场比较与情报 89% 正面

PriceLabs 强大的市场情报和价格购物工具可让用户高效地将自己的价格与竞争对手进行比较。该功能因提供关键的市场洞察而受到赞誉,使酒店经营者能够保持竞争力并... PriceLabs 强大的市场情报和价格购物工具可让用户高效地将自己的价格与竞争对手进行比较。该功能因提供关键的市场洞察而受到赞誉,使酒店经营者能够保持竞争力并响应市场状况。

酒店从业者提出异议的方面

改进空间:附加功能 76% 负面

一些反馈建议增加特定功能,例如更好的基本价格调整自动化和更强大的历史数据分析。这些改进可以为用户提供更深入的见解并进一步简化操作。

排名更高的方面

中型(25-74 间客房) #23 vs #43
小型(10-24 间客房) #21 vs #34
精品酒店 #27 vs #43
品牌/连锁酒店 #25 vs #43

独特功能

备用住宿日期建议 事件数据 STR 数据
4.8/5 易用性 5.0/5 客户支持 36 个集成
查看资料

关于 Automatic Pricing (by Dataria) 与 PriceLabs 的常见问题

Automatic Pricing (by Dataria) 能否替代 PriceLabs?

这取决于您的需求。Automatic Pricing (by Dataria) 和 PriceLabs 共享许多核心 Revenue Management Systems 功能,但各有独特的能力。Automatic Pricing (by Dataria) 提供 3 个经验证的集成合作伙伴,而 PriceLabs 提供 36 个。在切换之前,请查看上方的功能对比以了解它们的差异。

哪个更适合小型或独立酒店?

小型酒店应优先考虑易用性和快速入职。PriceLabs 在易用性方面领先,评分为 4.8/5 对比 4.7/5。寻找透明定价以及试用或演示选项。在各产品页面上按物业规模筛选评价,了解与您类似的酒店的反馈。

Automatic Pricing (by Dataria) 或 PriceLabs 是否提供免费方案?

Automatic Pricing (by Dataria):否。PriceLabs:否。 两款产品目前均不提供免费版。大多数 Revenue Management Systems 供应商提供演示或试用——在做出承诺之前,请分别向各供应商申请体验。

HTR 如何评估和排名 Automatic Pricing (by Dataria) 和 PriceLabs?

HT Score 是一个综合排名,考虑 4 个标准组和十多个变量,帮助酒店从业者客观比较酒店科技产品。Dataria 的 HT Score 为 0,PriceLabs 的为 75。以下是评分的计算方式。

标准组 权重 衡量内容
客户评分与评价

用户对该产品的推荐度如何?

评分分数、评价数量、声量份额、评价深度、评价时效性、成功案例

权重最高的因素。分析平均满意度评分(推荐可能性、易用性、支持、投资回报率)、相对于同类产品的评价总数、评价时效性(最近 6 个月内至少 20 条评价)以及跨独立酒店客户的声量份额以检测选择偏差。

合作伙伴生态系统

技术合作伙伴对该公司的推荐度如何?

合作伙伴推荐、集成数量、集成质量

评估合作伙伴推荐作为专家信心投票、经验证集成的数量以及生态系统质量——集成合作伙伴的平均 HT Score。拥有更高质量集成生态系统的产品更有可能提供互联互通的技术栈。

以客户为中心

该组织以客户为中心的程度如何?

认证支持、评价一致性、资料完整性

评估公司是否获得 HTR 客户支持认证、是否保持持续的评价收集(反馈驱动文化的指标)以及产品资料是否完整,包括功能、截图、定价和特性。

覆盖范围、持久力与资源

该公司的覆盖范围和资源有多广泛?

地理覆盖、持久力、公司资源、趋势评分

衡量全球覆盖(服务的国家和区域)、经营年限作为稳定性指标、团队规模作为资源指标,以及基于近十二个月买家咨询、评价、合作伙伴推荐和媒体活动的趋势评分。

客户评分和评价是 HT Score 算法中最重要的因素。HTR 不接受付费以提高排名。所有评价均经过验证——只有经确认从属关系的酒店行业从业者才能提交评分。 查看完整 HT Score 评估方法 →

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