市場調査レポート

商品コード

1800915

リテールアナリティクス市場レポート：機能、コンポーネント、展開モード、エンドユーザー、地域別、2025年～2033年

Retail Analytics Market Report by Function, Component, Deployment Mode, End User, and Region 2025-2033

出版日: 2025年08月01日
発行: IMARC
ページ情報: 英文 147 Pages
納期: 2～3営業日

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概要
図表
目次

概要

サンプル依頼リストに入れる

世界のリテールアナリティクスの市場規模は2024年に104億米ドルに達しました。今後、IMARC Groupは、2033年には452億米ドルに達し、2025年から2033年にかけて16.92%の成長率（CAGR）を示すと予測しています。北米は、先進的な技術インフラと大手小売企業の強力なプレゼンスが市場を牽引しています。リテールアナリティクス市場は、組織におけるデジタル化の拡大、クラウドベースのリテールアナリティクスソリューションの利用増加、時間と費用の節約を求める消費者のオンラインショッピング習慣の高まりによって大きな成長を遂げています。

リテールアナリティクス業界は、戦略的選択やビジネスプロセスの改善におけるデータ依存の高まりに後押しされ、大きな変化を経験しています。持続可能性は急速に小売戦略の主流になりつつあり、アナリティクスは環境の監視と報告に役立っています。小売企業はカーボンフットプリントを定量化し、エネルギー消費量を報告し、サプライチェーンパートナーの持続可能性を評価しています。アナリティクスはまた、廃棄物の削減、グリーン製品の推奨、倫理的な調達といった取り組みも支援しています。アナリティクスを持続可能な目標に統合することで、小売企業はより強固なブランド評価を確立するとともに、責任あるビジネスに対する顧客の期待に応えています。

リテールアナリティクス市場動向：

パーソナライズされた顧客体験へのニーズの高まり

小売企業は、顧客にパーソナライズされた体験を提供することを常に重視しており、これがリテールアナリティクスソリューションの利用を大きく後押ししています。その結果、多くの企業がパーソナライズされた小売ソリューションを発表しています。例えば、アップルは2025年にインドでShop with a Specialist over Videoを導入し、アップル製品をアップルストアでオンラインショッピングできるようにしました。オンライン・サーフィンの履歴、購買習慣、ロイヤリティ・スキーム、ソーシャルメディアの利用状況など、複数の情報源から情報を収集することで、企業は高度にカスタマイズされたマーケティング・プログラムを作成しています。リテールアナリティクスソリューションは、小売業者がより効率的に買い物客をセグメント化し、嗜好を予測し、それに基づいて商品の提案やオファーをパーソナライズすることを支援しています。顧客の間でパーソナライズされたショッピングへの期待が高まる中、小売企業はエンゲージメントと満足度を高めるために高度な分析ソリューションを活用しています。リアルタイム・パーソナライゼーションは競争上の優位性として台頭しており、企業はダイナミック・プライシングやパーソナライズされたオファーを活用して売上を伸ばしています。小売企業はまた、アナリティクス・プラットフォームにAIやMLを組み込み、精度の向上と意思決定の自動化を図っています。この動向は、オムニチャネル・リテールが勢いを増すにつれて加速しており、アナリティクス・プラットフォームは、カスタマージャーニーを最適化するために、物理チャネルとデジタルチャネルの両方で常にデータを収集しています。

eコマースとデジタルチャネルの急成長

オンライン小売業とデジタルチャネルの継続的な成長により、膨大な量のデータが生み出され、小売業者はそれを読み解くために高度なアナリティクスを導入するようになりました。顧客のオンラインショッピングへの移行が進む中、小売企業は、クリックスルー率、カート放棄、セッションの長さ、リピート訪問など、顧客の行動に関する豊富な情報を収集しています。リテールアナリティクスソフトウェアは、このようなオンライン上のやり取りをリアルタイムで監視し、企業がウェブサイトのデザインを改善したり、商品の露出を高めたり、ユーザー体験をさらに向上させたりできるよう、現在採用されています。モバイルショッピングやアプリを使った小売業も増えており、様々なデジタルプラットフォームで分析の可能性が広がっています。小売企業はデータインサイトの活用により、顧客獲得の強化、継続率の向上、デジタルマーケティングキャンペーンの改善を図っています。このようなシナリオの変化の中で、主要業績評価指標（KPI）の追跡、市場動向の把握、顧客行動への事前対応には、リアルタイム・アナリティクスが必要不可欠になり始めています。IMARC Groupは、世界のeコマース市場は2033年までに214兆5,000億米ドルに達すると予測しています。

人工知能（AI）と機械学習（ML）の進歩

人工知能（AI）と機械学習（ML）技術は、ビジネスに深い洞察をもたらし、複雑なプロセスを自動化するのに役立ち、リテールアナリティクス業界に革命をもたらしています。小売企業はAIベースの分析ソリューションを積極的に活用し、需要の予測、不正行為の特定、新たな動向の認識などを高い精度で行っています。MLアルゴリズムは常にビッグデータセットに働きかけ、根本的なパターンを特定し、価格戦略を洗練させ、リアルタイムで商品を提案しています。これらのテクノロジーは、スマートなチャットボットやバーチャルアシスタントによって顧客サービスも変えつつあり、データ主導の洞察に基づいて顧客の質問に答えたり、購入を促したりしています。小売企業はAIを活用して在庫の必要性を予測し、無駄を省くことで在庫管理を強化しています。また、AIが可能にする処方的分析は、予測結果に基づいて最適な行動を推奨することで、より戦略的な意思決定を促進しています。こうした技術の進歩が進む中、小売企業は、刻々と変化する市場環境の中で競争力と機動力を維持するため、AIを活用したアナリティクスへの投資を進めています。2025年、Standard AIはVision Analyticsを発表し、個人、商品、インタラクションの比類ない明瞭さによって得られる消費者行動、商品効果、店舗運営に関する洞察で小売業者やブランドを支援します。

リテールアナリティクス市場促進要因：

オムニチャネル小売戦略の統合

オムニチャネルリテール戦略は小売企業によって本格的に取り上げられつつあり、アナリティクスは、さまざまなタッチポイントでシームレスな顧客体験を提供する能力の中心となっています。顧客は、物理的なインタラクション、ウェブサイトでのインタラクション、スマートフォンアプリでのインタラクション、ソーシャルメディアでのインタラクションを組み合わせたマルチチャネル環境でブランドとやり取りしており、小売企業はこれらすべてのソースからデータを収集し、顧客体験の統合ビューを構築しています。リテールアナリティクスソリューションにより、企業はチャネル全体の行動を監視し、ドロップオフポイントを決定し、チャネルのパフォーマンスを最大化することができます。例えば、オンラインを閲覧していた顧客が、その後店舗に来店して購入する場合、アナリティクス・プラットフォームはそのような行動を監視し、マーケティングや営業活動に影響を与えます。店舗はまた、プロモーションの調整、クロスチャネルの在庫管理、フルフィルメントの効率最適化にもオムニチャネル・アナリティクスを活用しています。このようなアプローチにより、企業はマーケティング、オペレーション、顧客サービスのイニシアチブを調整し、最終的にブランドの一貫性と消費者の満足度を最大化することができます。デジタル小売と実店舗小売の2つの世界が融合し続ける中、オムニチャネル・アナリティクスの導入は着実にスピードを増しています。

サプライチェーンの最適化と効果的な在庫管理

小売企業は、サプライチェーンオペレーションと在庫管理をより最適化するためにアナリティクスを継続的に適用しており、これも市場を促進する要因の一つとなっています。迅速かつ正確な商品配送に対する顧客の期待が高まる中、リアルタイムのデータインサイトは、需要予測、在庫量の見直し、より効率的なロジスティクス管理に活用されています。リテールアナリティクスソフトウェアは、倉庫と店舗間の商品の流れを監視し、企業が過剰在庫を削減し、在庫切れを最小限に抑え、補充精度を向上させることを可能にしています。予測モデルは、過去の実績や季節パターンに基づいて、最適な注文サイズや配送スケジュールを決定するために使用されています。地理空間アナリティクスはまた、倉庫の位置や配送ルートを最適化することで、輸送費を最小限に抑え、サービスレベルを最大化するために小売業者によって採用されています。アナリティクスは、サプライヤーの業績追跡、リードタイムの監視、サプライチェーンのリスク評価にも活用されています。調達や在庫計画におけるデータ主導の意思決定を通じて、小売企業は収益性だけでなく経営効率も高めています。世界中で消費者の需要が変化し、サプライチェーンが寸断される環境では、こうした能力がますます必要になっています。

クラウドベースのアナリティクスソリューションの利用増加

クラウドベースのアナリティクス・プラットフォームは拡張性、柔軟性、コスト効率が高いため、小売企業の利用が増加しています。これらのプラットフォームにより、企業はオンプレミスの重いインフラを必要とすることなく、膨大な量のデータを取得、処理、分析できるようになっています。クラウドベースのリテールアナリティクスソリューションは、リアルタイムの洞察、迅速な展開、現在の企業システムとのシンプルな統合を実現しています。企業はこれらのソリューションを利用して、部門間の連携、データへのリモートアクセス、レポートの一貫性の確保を行っています。クラウドへの移行により、データ・セキュリティとコンプライアンスも強化されています。なぜなら、トップ・ベンダーは強力な暗号化を提供し、世界なデータ・プライバシー規制に従っているからです。また、クラウドプラットフォームは、ハイエンドのコンピューティング機能を従量課金制で提供することで、AIやMLの利用を容易にしています。小売企業は、初期投資を最小限に抑え、より俊敏な拡張を可能にするサブスクリプションベースのオプションから利益を得ています。デジタルトランスフォーメーションが加速する中、クラウドベースのアナリティクスは、小売業におけるイノベーションと競合差別化の重要な原動力として台頭しつつあります。

北米
- 米国
- カナダ
アジア太平洋地域
- 中国
- 日本
- インド
- 韓国
- オーストラリア
- インドネシア
- その他
欧州
- ドイツ
- フランス
- 英国
- イタリア
- スペイン
- ロシア
- その他
ラテンアメリカ
- ブラジル
- メキシコ
- その他
中東・アフリカ

第11章 SWOT分析

第12章バリューチェーン分析

第13章ポーターのファイブフォース分析

第14章価格分析

第15章競合情勢

市場構造
主要企業
主要企業のプロファイル
- 1010data Inc.（Advance Publications Inc.）
- Adobe Inc.
- Altair Engineering Inc.
- Flir Systems Inc.
- Fujitsu Limited
- International Business Machines Corporation
- Information Builders Inc.
- Microsoft Corporation
- Microstrategy Incorporated
- Oracle Corporation
- Qlik Technologies Inc.（Thoma Bravo LLC）
- SAP SE
- SAS Institute Inc.
- Tableau Software LLC（Salesforce.com Inc.）
- Tibco Software Inc.

図表

List of Figures

Figure 1: Global: Retail Analytics Market: Major Drivers and Challenges
Figure 2: Global: Retail Analytics Market: Sales Value (in Billion USD), 2019-2024
Figure 3: Global: Retail Analytics Market: Breakup by Function (in %), 2024
Figure 4: Global: Retail Analytics Market: Breakup by Component (in %), 2024
Figure 5: Global: Retail Analytics Market: Breakup by Deployment Mode (in %), 2024
Figure 6: Global: Retail Analytics Market: Breakup by End User (in %), 2024
Figure 7: Global: Retail Analytics Market: Breakup by Region (in %), 2024
Figure 8: Global: Retail Analytics Market Forecast: Sales Value (in Billion USD), 2025-2033
Figure 9: Global: Retail Analytics (Customer Management) Market: Sales Value (in Million USD), 2019 & 2024
Figure 10: Global: Retail Analytics (Customer Management) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 11: Global: Retail Analytics (In-store Operation) Market: Sales Value (in Million USD), 2019 & 2024
Figure 12: Global: Retail Analytics (In-store Operation) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 13: Global: Retail Analytics (Strategy and Planning) Market: Sales Value (in Million USD), 2019 & 2024
Figure 14: Global: Retail Analytics (Strategy and Planning) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 15: Global: Retail Analytics (Supply Chain Management) Market: Sales Value (in Million USD), 2019 & 2024
Figure 16: Global: Retail Analytics (Supply Chain Management) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 17: Global: Retail Analytics (Marketing and Merchandizing) Market: Sales Value (in Million USD), 2019 & 2024
Figure 18: Global: Retail Analytics (Marketing and Merchandizing) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 19: Global: Retail Analytics (Other Functions) Market: Sales Value (in Million USD), 2019 & 2024
Figure 20: Global: Retail Analytics (Other Functions) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 21: Global: Retail Analytics (Software) Market: Sales Value (in Million USD), 2019 & 2024
Figure 22: Global: Retail Analytics (Software) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 23: Global: Retail Analytics (Services) Market: Sales Value (in Million USD), 2019 & 2024
Figure 24: Global: Retail Analytics (Services) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 25: Global: Retail Analytics (On-premises) Market: Sales Value (in Million USD), 2019 & 2024
Figure 26: Global: Retail Analytics (On-premises) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 27: Global: Retail Analytics (Cloud-based) Market: Sales Value (in Million USD), 2019 & 2024
Figure 28: Global: Retail Analytics (Cloud-based) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 29: Global: Retail Analytics (Small and Medium Enterprises) Market: Sales Value (in Million USD), 2019 & 2024
Figure 30: Global: Retail Analytics (Small and Medium Enterprises) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 31: Global: Retail Analytics (Large Enterprises) Market: Sales Value (in Million USD), 2019 & 2024
Figure 32: Global: Retail Analytics (Large Enterprises) Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 33: North America: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 34: North America: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 35: United States: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 36: United States: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 37: Canada: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 38: Canada: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 39: Asia Pacific: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 40: Asia Pacific: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 41: China: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 42: China: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 43: Japan: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 44: Japan: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 45: India: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 46: India: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 47: South Korea: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 48: South Korea: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 49: Australia: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 50: Australia: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 51: Indonesia: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 52: Indonesia: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 53: Others: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 54: Others: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 55: Europe: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 56: Europe: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 57: Germany: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 58: Germany: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 59: France: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 60: France: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 61: United Kingdom: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 62: United Kingdom: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 63: Italy: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 64: Italy: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 65: Spain: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 66: Spain: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 67: Russia: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 68: Russia: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 69: Others: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 70: Others: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 71: Latin America: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 72: Latin America: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 73: Brazil: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 74: Brazil: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 75: Mexico: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 76: Mexico: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 77: Others: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 78: Others: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 79: Middle East and Africa: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
Figure 80: Middle East and Africa: Retail Analytics Market Forecast: Breakup by Country (in %), 2024
Figure 81: Middle East and Africa: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
Figure 82: Global: Retail Analytics Industry: SWOT Analysis
Figure 83: Global: Retail Analytics Industry: Value Chain Analysis
Figure 84: Global: Retail Analytics Industry: Porter's Five Forces Analysis

List of Tables

Table 1: Global: Retail Analytics Market: Key Industry Highlights, 2024 and 2033
Table 2: Global: Retail Analytics Market Forecast: Breakup by Function (in Million USD), 2025-2033
Table 3: Global: Retail Analytics Market Forecast: Breakup by Component (in Million USD), 2025-2033
Table 4: Global: Retail Analytics Market Forecast: Breakup by Deployment Mode (in Million USD), 2025-2033
Table 5: Global: Retail Analytics Market Forecast: Breakup by End User (in Million USD), 2025-2033
Table 6: Global: Retail Analytics Market Forecast: Breakup by Region (in Million USD), 2025-2033
Table 7: Global: Retail Analytics Market Structure
Table 8: Global: Retail Analytics Market: Key Players

Product Code: SR112025A2372

The global retail analytics market size reached USD 10.4 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 45.2 Billion by 2033, exhibiting a growth rate (CAGR) of 16.92% during 2025-2033. North America leads the market, driven by advanced technology infrastructure and the strong presence of major retail players. The retail analytics market is experiencing significant growth driven by the expanding digitization in organizations, rising use of cloud-based retail analytics solutions, and growing online shopping habits of consumers looking to save time and money.

The retail analytics industry is experiencing strong change, fueled by growing dependence on data for strategic choice and business process improvement. Sustainability is fast becoming mainstream retail strategy, and analytics is helping to monitor and report on the environment. Retailers are quantifying carbon footprints, reporting on energy consumption, and assessing the sustainability of supply chain partners. Analytics is also backing efforts like waste reduction, green product recommendations, and ethical sourcing. By integrating analytics with sustainable objectives, retailers are building a stronger brand reputation as well as addressing customer expectations for responsible business.

Retail Analytics Market Trends:

Growing Need for Personalized Customer Experience

Retailers are constantly emphasizing providing customers with very personalized experiences, and this is greatly pushing the usage of retail analytics solutions. As a result, a lot of companies are launching personalized retail solutions. For example, in 2025, Apple introduced Shop with a Specialist over Video in India, where people can shop online for apple products on the Apple Store. By gathering information from multiple sources like online surfing history, buying habits, loyalty schemes, and social media usage, companies are creating highly tailored marketing programs. Retail analytics solutions are assisting retailers to segment shoppers more efficiently, forecast tastes, and personalize product suggestions and offers based on that. With rising expectations for personalized shopping among customers, retailers are using sophisticated analytics solutions to drive engagement and satisfaction. Real-time personalization is emerging as a competitive advantage, with companies leveraging dynamic pricing and personalized offers to boost sales. Retailers are also embedding AI and ML into analytics platforms to improve accuracy and automate decision-making. The trend is speeding up as omnichannel retail gains momentum, with analytics platforms constantly gathering data both in physical and digital channels to optimize the customer journey.

Sudden Boom in E-Commerce and Digital Channels

The continuing growth of online retailing and digital channels is creating vast amounts of data, leading retailers to embrace advanced analytics to decipher it. With customers increasingly turning to online shopping, retailers are gathering rich information about customer behavior, such as click-through rates, cart abandonment, session length, and repeat visits. Retail analytics software is now being employed to monitor these online interactions in real-time so that companies can enhance website designs, enhance product exposure, and make user experience even better. With mobile shopping and app-based retailing also increasing, the analytics potential is expanding on various digital platforms. Retailers are utilizing data insights to enhance customer acquisition, increase retention rates, and refine their digital marketing campaigns. In this changing scenario, real-time analytics is starting to become a necessity to track key performance indicators (KPIs), identify market trends, and react in advance to customer behavior. IMARC Group predicts that the global e-commerce market is projected to attain USD 214.5 Trillion by 2033.

Artificial Intelligence (AI) and Machine Learning (ML) advancements

Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the retail analytics industry, helping businesses gain deeper insights and automate intricate processes. Retailers are using AI-based analytics solutions actively to predict demand, identify fraud, and recognize emerging trends with great accuracy. ML algorithms are constantly working on big data sets to identify underlying patterns, refine pricing strategies, and suggest products in real-time. These technologies are also changing customer service with smart chatbots and virtual assistants, which are answering customer questions and facilitating purchases based on data-driven insights. Retailers are using AI to enhance inventory management by forecasting stock needs and reducing waste. Also, prescriptive analytics enabled by AI is facilitating more strategic decision-making by recommending the optimal course of action based on predictive outcomes. As these technologies proceed to advance, retailers are investing in AI-powered analytics to remain competitive and agile in an ever-changing market landscape. In 2025, Standard AI launched Vision Analytics empowers retailers and brands with insights into consumer behavior, product effectiveness, and store operations obtained through unmatched clarity of individuals, products, and interactions.

Retail Analytics Market Growth Drivers:

Omnichannel Retail Strategies Integration

Omnichannel retail strategies are being picked up by retailers in earnest, and analytics is at the center of their ability to provide seamless customer experiences across various touch points. Customers are interacting with brands in a multichannel environment combining physical interaction, website interaction, smartphone app interaction, and social media interaction, and retailers are gathering data from all these sources to build an integrated view of the customer experience. Retail analytics solutions are allowing companies to monitor behavior across channels, determine drop-off points, and maximize channel performance. For instance, a customer who is browsing online will subsequently come into a store to make a purchase, and analytics platforms are monitoring such behaviors to influence marketing and sales efforts. Stores are also leveraging omnichannel analytics for coordinating promotions, for cross-channel inventory management, and optimizing the efficiency of fulfillment. Such an approach is allowing companies to align their marketing, operations, and customer service initiatives to ultimately maximize brand consistency and consumer satisfaction. As the two worlds of digital and physical retail continue to merge, adoption of omnichannel analytics continues to gain speed steadily.

Supply Chain Optimization and Effective Inventory Management

Retailers are continuously applying analytics for better optimization of supply chain operations and inventory management, which is another key driver of the market. In an era of rising customer expectations to speedily and accurately deliver products, real-time data insights are being used to forecast demand, review stock quantities, and manage logistics more efficiently. Retail analytics software is monitoring product flow between warehouses and stores, allowing companies to cut overstocking, minimize stockouts, and improve replenishment accuracy. Predictive models are being used to determine the best order sizes and distribution schedules based on past performance and seasonal patterns. Geospatial analytics are also being employed by retailers to minimize transportation expenses and maximize service levels by optimizing warehouse positions and delivery routes. Analytics is also being utilised to track performance of suppliers, monitor lead times, and assess risks in supply chains. Through data-driven decision-making in procurement and inventory planning, retailers are enhancing operational effectiveness as well as profitability. These capabilities are becoming more of a necessity in an environment of changing consumer demand and supply chain disruptions across the world.

Increasing Use of Cloud-Based Analytics Solutions

Retailers are increasingly using cloud-based analytics platforms because they are scalable, flexible, and cost-effective. These platforms are allowing companies to capture, process, and analyze huge amounts of data without the need for heavy on-premise infrastructure. Cloud-based retail analytics solutions are giving real-time insights, quicker deployment, and simpler integration with current enterprise systems. Companies are using these solutions to work inter-departmentally, get remote access to data, and ensure consistency of reports. The move to cloud is also tightening data security and compliance because top vendors provide high-strength encryption and follow global data privacy regulations. Cloud platforms are also making it easy to use AI and ML by providing high-end computing capabilities on a pay-as-you-use basis. Retailers are gaining from subscription-based options that minimize initial investment and enable more agility in scaling up. As digital transformation gathers pace, cloud-based analytics is emerging as a key driver of innovation and competitive differentiation in retail.

Retail Analytics Market Segmentation:

Breakup by Function:

Customer Management
In-store Operation
Strategy and Planning
Supply Chain Management
Marketing and Merchandizing
Others

Customer management accounts for the majority of the market share

Due to the growing demand for individualized customer experiences and the strategic significance of customer loyalty and retention in a cutthroat retail environment, customer management leads the retail analytics market by function. Retailers may deliver customized marketing, improve customer interactions, and expand their service offerings by using analytics to obtain deep insights into customer behaviors, preferences, and purchasing habits. For instance, the Census Bureau data shows significant insights into retail sales and e-commerce trends which are crucial for customer management in retail analytics. In addition, the Annual Retail Trade Survey provides detailed annual sales, e-commerce sales, and inventories across various retail sectors. This can help businesses understand consumer buying patterns and adapt their customer management strategies accordingly. This data-driven strategy aids in the identification of valuable clients, forecasting their future purchasing patterns and putting in place efficient loyalty schemes. Furthermore, by facilitating real-time decision-making and predictive analytics, the incorporation of technologies like artificial intelligence (AI) and machine learning further augments the efficacy of these techniques.

Breakup by Component:

Software
Services

Software holds the largest share of the industry

Software dominates the retail analytics industry as it is crucial to turning massive volumes of data into insights that can be put into practice, which helps retailers make better decisions. The U.S. Census Bureau reports that in Q12021, e-commerce sales made up almost 13% of overall sales, highlighting the significance of analytics in maximizing online sales tactics. In today's data-driven market climate, retail analytics software offers extensive solutions for customer behavior monitoring, inventory management, and sales forecasting. The growing use of digital operations in retail, as noted by the Bureau of Labor Statistics, calls for advanced analytics solutions to manage the scope and intricacy of contemporary retail operations.

Breakup by Deployment Mode:

On-premises
Cloud-based

Cloud-based represents the leading market segment

Due to their scalability, flexibility, and affordability-all of which are critical for managing the enormous volumes of data created by contemporary retail operations-cloud-based solutions provide a positive impact on the retail analytics industry outlook. Retailers are able to efficiently handle peak shopping periods because they have the flexibility to scale resources up or down as needed. A U.S. Small Business Administration survey states that as cloud computing can lower IT overhead expenses and increase operational efficiency, small and medium-sized firms are adopting it at an increasing rate. This change is particularly important for the retail industry, where real-time data processing and analytics are required due to changing market conditions. Cloud systems make this possible by offering data storage and sophisticated analysis capabilities without requiring a substantial initial outlay of funds.

Breakup by End User:

Small and Medium Enterprises
Large Enterprises

Large enterprises exhibit a clear dominance in the market

Due to their vast operational scope and the intricate data environments, they oversee, large organizations hold a dominant position in the end-user retail analytics market. These companies possess the infrastructure and financial means to invest in cutting-edge retail analytics solutions, which are essential for managing the enormous volumes of data produced across numerous channels and regions. Large businesses may learn a great deal about market trends, supply chain efficiency, and consumer behavior by integrating and analyzing this data. Strategic planning, competitiveness in international markets, and operational optimization all depend on this degree of analytics. Large businesses can also frequently use more advanced analytics, such as AI-driven tools and predictive modeling, to spur innovation and enhance consumer experiences.

Breakup By Region:

North America
- United States
- Canada
Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Others
Europe
- Germany
- France
- United Kingdom
- Italy
- Spain
- Russia
- Others
Latin America
- Brazil
- Mexico
- Others
Middle East and Africa

North America leads the market, accounting for the largest retail analytics market share

The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America represented the largest market for retail analytics.

North America dominates the retail analytics market due to its sophisticated technological infrastructure, there has been a widespread use of big data solutions, and large investments in artificial intelligence (AI) and machine learning. The U.S. Department of Commerce reports that North American retail e-commerce sales increased 32.4% in 2019 compared to 2020, indicating the sector's rapid expansion and the growing demand for advanced analytics. Large digital organizations and startups that specialize in retail analytics solutions to improve customer experiences and operational efficiency call this region home. According to the U.S. Bureau of Economic Analysis, the demand for analytics to comprehend consumer behavior, manage inventory, and improve supply chains is driven by the digital transformation in retail. This is further catalyzing the retail analytics market growth.

Competitive Landscape:

The retail analytics market research report has also provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the major market players in the retail analytics industry include 1010data Inc. (Advance Publications Inc.), Adobe Inc., Altair Engineering Inc., Flir Systems Inc., Fujitsu Limited, International Business Machines Corporation, Information Builders Inc., Microsoft Corporation, Microstrategy Incorporated, Oracle Corporation, Qlik Technologies Inc. (Thoma Bravo LLC), SAP SE, SAS Institute Inc., Tableau Software LLC (Salesforce.com Inc.), Tibco Software Inc, etc.

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Some of the leading companies in the retail analytics space, such as Microsoft Corporation, Fujitsu Limited, Flir Systems Inc., Altair Engineering Inc., Adobe Inc., and 1010data Inc., are constantly improving their products to increase the retail analytics market value. 1010data Inc. is a cloud-based analytics provider with a strong emphasis on retail operations optimization. Adobe Inc. provides customized digital marketing solutions through its advanced Adobe Analytics platform. Retailers can enhance supply chain and inventory management with the assistance of Altair Engineering Inc., which incorporates analytics into product design. Flir Systems Inc. uses cutting-edge thermal imaging technology to gain insights into customer behavior and security. Complete retail solutions, such as data-driven point-of-sale systems, are provided by Fujitsu Limited. Microsoft Corporation, is advancing the personalization of shopping experiences by leveraging cutting-edge AI and cloud-based technologies to improve customer engagement. Collectively, these businesses are paving the way for sophisticated, data-driven retail strategy. For instance, Adobe Experience Platform delivered new tools such as customer journey analytics with which retailers can now leverage AI to detect broken experiences (or to uncover new opportunities). This update takes anomaly detection beyond the website - where it has been predominantly used - and allows brands to see where issues arise as shoppers move between channels.

Key Questions Answered in This Report

1.What was the size of the global retail analytics market in 2024?
2.What is the expected growth rate of the global retail analytics market during 2025-2033?
3.What are the key factors driving the global retail analytics market?
4.What has been the impact of COVID-19 on the global retail analytics market?
5.What is the breakup of the global retail analytics market based on the function?
6.What is the breakup of the global retail analytics market based on the component?
7.What is the breakup of the global retail analytics market based on the deployment mode?
8.What is the breakup of the global retail analytics market based on the end user?
9.What are the key regions in the global retail analytics market?
10.Who are the key players/companies in the global retail analytics market?

1 Preface

2 Scope and Methodology

2.1 Objectives of the Study
2.2 Stakeholders
2.3 Data Sources
- 2.3.1 Primary Sources
- 2.3.2 Secondary Sources
2.4 Market Estimation
- 2.4.1 Bottom-Up Approach
- 2.4.2 Top-Down Approach
2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

4.1 Overview
4.2 Key Industry Trends

5 Global Retail Analytics Market

5.1 Market Overview
5.2 Market Performance
5.3 Impact of COVID-19
5.4 Market Forecast

6 Market Breakup by Function

6.1 Customer Management
- 6.1.1 Market Trends
- 6.1.2 Market Forecast
6.2 In-store Operation
- 6.2.1 Market Trends
- 6.2.2 Market Forecast
6.3 Strategy and Planning
- 6.3.1 Market Trends
- 6.3.2 Market Forecast
6.4 Supply Chain Management
- 6.4.1 Market Trends
- 6.4.2 Market Forecast
6.5 Marketing and Merchandizing
- 6.5.1 Market Trends
- 6.5.2 Market Forecast
6.6 Others
- 6.6.1 Market Trends
- 6.6.2 Market Forecast

7 Market Breakup by Component

7.1 Software
- 7.1.1 Market Trends
- 7.1.2 Market Forecast
7.2 Services
- 7.2.1 Market Trends
- 7.2.2 Market Forecast

8 Market Breakup by Deployment Mode

8.1 On-premises
- 8.1.1 Market Trends
- 8.1.2 Market Forecast
8.2 Cloud-based
- 8.2.1 Market Trends
- 8.2.2 Market Forecast

9 Market Breakup by End User

9.1 Small and Medium Enterprises
- 9.1.1 Market Trends
- 9.1.2 Market Forecast
9.2 Large Enterprises
- 9.2.1 Market Trends
- 9.2.2 Market Forecast

10 Market Breakup by Region

10.1 North America
- 10.1.1 United States
  - 10.1.1.1 Market Trends
  - 10.1.1.2 Market Forecast
- 10.1.2 Canada
  - 10.1.2.1 Market Trends
  - 10.1.2.2 Market Forecast
10.2 Asia Pacific
- 10.2.1 China
  - 10.2.1.1 Market Trends
  - 10.2.1.2 Market Forecast
- 10.2.2 Japan
  - 10.2.2.1 Market Trends
  - 10.2.2.2 Market Forecast
- 10.2.3 India
  - 10.2.3.1 Market Trends
  - 10.2.3.2 Market Forecast
- 10.2.4 South Korea
  - 10.2.4.1 Market Trends
  - 10.2.4.2 Market Forecast
- 10.2.5 Australia
  - 10.2.5.1 Market Trends
  - 10.2.5.2 Market Forecast
- 10.2.6 Indonesia
  - 10.2.6.1 Market Trends
  - 10.2.6.2 Market Forecast
- 10.2.7 Others
  - 10.2.7.1 Market Trends
  - 10.2.7.2 Market Forecast
10.3 Europe
- 10.3.1 Germany
  - 10.3.1.1 Market Trends
  - 10.3.1.2 Market Forecast
- 10.3.2 France
  - 10.3.2.1 Market Trends
  - 10.3.2.2 Market Forecast
- 10.3.3 United Kingdom
  - 10.3.3.1 Market Trends
  - 10.3.3.2 Market Forecast
- 10.3.4 Italy
  - 10.3.4.1 Market Trends
  - 10.3.4.2 Market Forecast
- 10.3.5 Spain
  - 10.3.5.1 Market Trends
  - 10.3.5.2 Market Forecast
- 10.3.6 Russia
  - 10.3.6.1 Market Trends
  - 10.3.6.2 Market Forecast
- 10.3.7 Others
  - 10.3.7.1 Market Trends
  - 10.3.7.2 Market Forecast
10.4 Latin America
- 10.4.1 Brazil
  - 10.4.1.1 Market Trends
  - 10.4.1.2 Market Forecast
- 10.4.2 Mexico
  - 10.4.2.1 Market Trends
  - 10.4.2.2 Market Forecast
- 10.4.3 Others
  - 10.4.3.1 Market Trends
  - 10.4.3.2 Market Forecast
10.5 Middle East and Africa
- 10.5.1 Market Trends
- 10.5.2 Market Breakup by Country
- 10.5.3 Market Forecast

11 SWOT Analysis

11.1 Overview
11.2 Strengths
11.3 Weaknesses
11.4 Opportunities
11.5 Threats

12 Value Chain Analysis

13 Porters Five Forces Analysis

13.1 Overview
13.2 Bargaining Power of Buyers
13.3 Bargaining Power of Suppliers
13.4 Degree of Competition
13.5 Threat of New Entrants
13.6 Threat of Substitutes

14 Price Analysis

15 Competitive Landscape

15.1 Market Structure
15.2 Key Players
15.3 Profiles of Key Players
- 15.3.1 1010data Inc. (Advance Publications Inc.)
  - 15.3.1.1 Company Overview
  - 15.3.1.2 Product Portfolio
- 15.3.2 Adobe Inc.
  - 15.3.2.1 Company Overview
  - 15.3.2.2 Product Portfolio
  - 15.3.2.3 Financials
  - 15.3.2.4 SWOT Analysis
- 15.3.3 Altair Engineering Inc.
  - 15.3.3.1 Company Overview
  - 15.3.3.2 Product Portfolio
  - 15.3.3.3 Financials
- 15.3.4 Flir Systems Inc.
  - 15.3.4.1 Company Overview
  - 15.3.4.2 Product Portfolio
  - 15.3.4.3 Financials
  - 15.3.4.4 SWOT Analysis
- 15.3.5 Fujitsu Limited
  - 15.3.5.1 Company Overview
  - 15.3.5.2 Product Portfolio
  - 15.3.5.3 Financials
  - 15.3.5.4 SWOT Analysis
- 15.3.6 International Business Machines Corporation
  - 15.3.6.1 Company Overview
  - 15.3.6.2 Product Portfolio
  - 15.3.6.3 Financials
  - 15.3.6.4 SWOT Analysis
- 15.3.7 Information Builders Inc.
  - 15.3.7.1 Company Overview
  - 15.3.7.2 Product Portfolio
- 15.3.8 Microsoft Corporation
  - 15.3.8.1 Company Overview
  - 15.3.8.2 Product Portfolio
  - 15.3.8.3 Financials
  - 15.3.8.4 SWOT Analysis
- 15.3.9 Microstrategy Incorporated
  - 15.3.9.1 Company Overview
  - 15.3.9.2 Product Portfolio
  - 15.3.9.3 Financials
  - 15.3.9.4 SWOT Analysis
- 15.3.10 Oracle Corporation
  - 15.3.10.1 Company Overview
  - 15.3.10.2 Product Portfolio
  - 15.3.10.3 Financials
  - 15.3.10.4 SWOT Analysis
- 15.3.11 Qlik Technologies Inc. (Thoma Bravo LLC)
  - 15.3.11.1 Company Overview
  - 15.3.11.2 Product Portfolio
- 15.3.12 SAP SE
  - 15.3.12.1 Company Overview
  - 15.3.12.2 Product Portfolio
  - 15.3.12.3 Financials
  - 15.3.12.4 SWOT Analysis
- 15.3.13 SAS Institute Inc.
  - 15.3.13.1 Company Overview
  - 15.3.13.2 Product Portfolio
  - 15.3.13.3 SWOT Analysis
- 15.3.14 Tableau Software LLC (Salesforce.com Inc.)
  - 15.3.14.1 Company Overview
  - 15.3.14.2 Product Portfolio
- 15.3.15 Tibco Software Inc.
  - 15.3.15.1 Company Overview
  - 15.3.15.2 Product Portfolio
  - 15.3.15.3 SWOT Analysis

リテールアナリティクス市場レポート：機能、コンポーネント、展開モード、エンドユーザー、地域別、2025年～2033年

Retail Analytics Market Report by Function, Component, Deployment Mode, End User, and Region 2025-2033

リテールアナリティクス市場動向：

リテールアナリティクス市場促進要因：

目次

第1章 序文

第2章 調査範囲と調査手法

第3章 エグゼクティブサマリー

第4章 イントロダクション

第5章 世界のリテールアナリティクス市場

第6章 市場内訳：機能別

第7章 市場内訳：コンポーネント別

第8章 市場内訳：展開モード別

第9章 市場内訳：エンドユーザー別

第10章 市場内訳：地域別

第11章 SWOT分析

第12章 バリューチェーン分析

第13章 ポーターのファイブフォース分析

第14章 価格分析

第15章 競合情勢