Licensed for Distribution
Published 17 March 2021 - ID G00455035
By Stephen Emmott, Anthony Mullen
Insight engines combine search capabilities with artificial intelligence to deliver actionable insights derived from the full spectrum of content and data sourced within and external to an enterprise. This Magic Quadrant profiles 15 vendors to help application leaders make the best choice.
Market Definition/Description
Gartner defines insight engines as systems that apply relevancy methods to discover, describe, organize and analyze content and data. They enable preexisting or newly synthesized information to be delivered proactively or interactively, in context, to digital workers, customers and others at timely business moments.
Insight engines represent an evolution of search and natural language technologies (NLTs). They deliver information in context to people (content in context) and to support machine automation (data in context). They do this by connecting to varied sources and types of content (such as documents in content services platforms) and data (such as records in operational database management systems) in order to build an index of extracted data that can be queried by people and machines. Connectors and pre-index processing are used to gather and enrich data before it is indexed; touchpoints and post-query processing are used to simplify the experience for people. Insight engines should be viewed as platforms on which multiple insight applications are provided and developed.
Insight engines have the following core capabilities and characteristics:
Ability to include key data sources
Support for data enrichment
Delivery of results to various touchpoints
Evaluation and tuning of relevance
Security features
Query input flexibility
Insight engines have the following optional capabilities and characteristics:
Ability to analyze result sets
Architecture and deployment model
Ease of use (for administrators and subject matter experts)
Support for multiple languages
Personalization features
Magic Quadrant
Figure 1. Magic Quadrant for Insight Engines
Source: Gartner (March 2021)
Vendor Strengths and Cautions
Coveo
Coveo is a Leader in this Magic Quadrant. Its Coveo Relevance Platform product is broadly focused on self- and agent-assisted support in the context of digital commerce, CRM and IT service management.
Coveo is a privately owned company. Its operations are mostly in North America. Its headquarters is in Quebec City, Canada, and it has five more offices in North America and EMEA. Its partners, of which there are about 180, are primarily located in North America, with the majority providing professional services, in addition to reselling. Its customers come from a broad range of industries, but especially the communications, media and services, manufacturing and natural resources, and banking and securities sectors. Most of its customers are based in North America.
Coveo’s acquisition of Tooso in July 2019 suggests that the product will make deeper use of machine learning (ML) techniques, augmented by knowledge graphs, in order to go beyond usage-based ranking and improve natural language processing. Later the same year, Coveo announced its sixth funding round, resulting in further investment of $172 million.
Strengths
Sales Strategy: Coveo provides a rich set of productized integrations for sales and customer support in particular, and, as a result, can have a presence in third-party marketplaces. Notable integrations are with Salesforce, ServiceNow and Microsoft (Dynamics).
Product or Service: Coveo’s product offers a high-quality administrative experience, both natively and in third-party environments. The product provides simple-to-use indexing and enrichment tools, alongside clear relevance tuning and workflow.
Marketing Strategy: Mature marketing plans consistently deliver a clear value proposition throughout Coveo’s messaging, which targets the needs of well-defined buyer personas.
Cautions
Data enrichment (Product or Service): To date, Coveo’s utilization of natural language and semantic technologies has been limited, with heavy emphasis upon ML (to rerank results, for example). However, this is expected to change as a result of Coveo’s acquisition of Tooso, which may well enable new capabilities arising from ML moderated by knowledge graphs.
Vertical/Industry Strategy: Coveo’s success in functional domains centered on customer engagement enables it to reach all industries. However, its ability to penetrate other functional domains across industries limits its applicability as a vendor of situational technology.
Geographic Strategy: In terms of the location of its offices, partners and customers, Coveo’s presence tends toward North America. Outside North America, Coveo is present mainly in EMEA, specifically Western Europe.
Elastic
Elastic is a Challenger and a new entrant in this Magic Quadrant. The Elastic Enterprise Search product, comprising Workplace Search, App Search and Site Search, is focused on supporting customer experiences in the context of digital commerce, and on the employees who support those experiences.
Elastic is a publicly traded company. Its operations are geographically dispersed, with principal headquarters in Mountain View, California, U.S., regional headquarters in Amsterdam, Netherlands, and Singapore, plus 30 more offices in North America, EMEA and Asia/Pacific. Its partners, of which there are about 170, are geographically dispersed, with the majority providing professional services or intellectual property (IP) development, in addition to their reselling activities. Elastic’s customers come from a broad range of industries, but tend to be in the communications, media and services, insurance, and retail sectors. The majority of Elastic’s customers are based in North America.
Elastic plans to unify the data indexes underpinning its different product categories (search, observability and security), thereby extending the use cases each can serve (to include, for example, facilitation of data governance).
Strengths
Business Model: With a download of the product available from Elastic’s website, there is no obstacle to organizations and their partners trying Elastic’s offering. This partly reflects the vendor’s elevated presence in the market with respect to marketing execution.
Innovation: Elastic has leading and easy-to-use ML model creation, management and training to support things like anomalies and temporal sensitivities, and to provide explainability. In addition, its open-source status results in a rich developer community that end users can draw on and learn from.
Multiple languages (Product or Service): Elastic supports more languages than most of the vendors in this Magic Quadrant. Furthermore, Elastic’s product supports the highest proportion of languages at a semantic level of analysis for indexing and querying.
Cautions
Vertical/Industry Strategy: Elastic lacks vertical offerings that provide industry support — an important consideration for nondeveloper buyers. Instead, Elastic’s partners supply this expertise through their development of IP.
Business Model: In contrast to other vendors in this market, Elastic bases its pricing model on compute resources. Although Elastic offers an easy-to-use pricing calculator, comparison during procurement or review, and forecasting of costs and budgets, can be challenging.
Offering (Product) Strategy: Elastic has now begun to productize its offering in order to build on its bottom-up approach that is driven by developers. But the vision for, and the positioning of, its product appear somewhat weak in comparison to those of the competition. Missing is a broader vision for search and the pivotal role it can play in the wider NLT market.
EPAM
EPAM is a Niche Player in this Magic Quadrant. Its InfoNgen product is focused on supporting strategic decision making from the analysis of varied external and internal content sources.
EPAM is a publicly traded company. Its operations are geographically dispersed, with headquarters in Newtown, Pennsylvania, U.S., plus 68 more offices in North America, EMEA, Latin America and Asia/Pacific. Its 12 partners are in North America and EMEA, with the majority providing professional services or IP development, in addition to their reselling activities. Its customers come from a broad range of industries, but especially the banking and securities, life sciences and healthcare products, and insurance sectors. The majority of EPAM’s customers are based in North America and EMEA.
EPAM is developing InfoNgen to index a broader range of content sources, such as images and video, and is expanding its natural language processing capabilities to include ML, in addition to emphasizing structured metadata and rule-based analysis.
Strengths
Vertical/Industry Strategy: EPAM has the broadest reach across industries of any vendor in this Magic Quadrant.
Sales Execution/Pricing: Although EPAM’s flexibility with respect to pricing model makes it challenging to compare prices, customers praise the vendor’s negotiation of product pricing. EPAM is principally a service provider, rather than a product company, so InfoNgen represents the productization of its service offering.
Customer Experience: Customer reviews on Gartner’s Peer Insights platform reveal high levels of satisfaction with the quality of InfoNgen and the professional services provided by EPAM. This is also the case for customer agility after deployment.
Cautions
Personalization (Product or Service): EPAM’s personalization capability could be improved with more context modeling and a role-centric approach that includes explicit cues and more granular workflow modeling for triggering insights.
Innovation: EPAM has the lowest score for innovation in this Magic Quadrant. Although it has deep expertise in semantic technologies, it makes less use — and less diverse use — of ML and neural networks than other vendors. It needs to accelerate innovation in areas such as the data pipeline, especially in relation to data enrichment and inclusion of key data sources.
Sales Strategy: EPAM has the lowest number of partners in this Magic Quadrant, which limits its reach via indirect channels, and geographically.
Expert.ai
Expert.ai is a Niche Player in this Magic Quadrant. Its product, NL Suite, comprises a set of proprietary natural language capabilities and products focused on extracting data from content to support automation and knowledge discovery.
Expert.ai is a publicly traded company. Its operations are mostly in EMEA. Its headquarters is in Modena, Italy, and it has 13 more offices in EMEA and North America. Its partners, of which there are about 40, are primarily located in EMEA. The majority provide professional services, in addition to their reselling activities, and a minority develop IP. Expert.ai’s customers come from a narrow range of industries and tend to be in the insurance, banking and securities, and national and international government sectors. Most of its customers are based in North America and EMEA.
Expert.ai’s offer extends beyond its insight engine product to a more comprehensive natural language suite. A richer set of NLT offerings is expected to accompany the existing offering.
Strengths
Vertical/Industry Strategy: Expert.ai has developed deeper custom offerings for key industries such as life sciences and insurance.
Offering (Product) Strategy: Expert.ai has built a strong foundation on semantic technologies, and expresses a broad vision for how NLTs will evolve, with insight engines being foundational elements.
Support for multiple languages (Product or Service): Although, of the vendors in this Magic Quadrant, Expert.ai supports the fewest languages, all 12 that it does support are supported natively at a deep semantic level for indexing and querying.
Cautions
Ability to connect to key data sources (Product or Service): Of the vendors in this Magic Quadrant, Expert.ai has the joint lowest number of connectors. Although its product is well-featured and well-placed for the evolution of insight engines, it is not a quick-start option for organizations with a broad or complex mix of data sources.
Marketing Strategy: Expert.ai’s marketing plans lack clarity with respect to buyers, their needs, and the value proposition that both vendor and product bring to the table.
Customer Experience: Judging by reviews on Gartner’s Peer Insights platform, Expert.ai’s customer satisfaction is lower than that of other vendors in this Magic Quadrant. The vendor has room to improve in areas like postdeployment agility — in other words, enabling clients to expand their use of its insight engine as a platform.
Funnelback
Funnelback is a Niche Player in this Magic Quadrant. Its product is also called Funnelback. The product’s principal use cases are site search, intranet search, case management, knowledge management and product management (retail).
Funnelback is a privately owned company. Its operations are mostly in Asia/Pacific, with its headquarters being in Canberra, Australia. Eleven more offices are located in Asia/Pacific, EMEA and North America. Its 13 partners are distributed across Asia/Pacific, EMEA and North America, and about half provide professional services, in addition to their reselling activities. Its customers come from a narrow range of industries, especially higher education, government and banking. Most of its customers are based in Asia/Pacific and EMEA.
Funnelback plans to extend the number and depth of its packaged solutions with knowledge graph integration and to provide analytics plug-ins and natural language question answering tailored to sectors. It also plans to attract more OEM and solution partners to support this activity in order to consolidate the value it provides in the government and higher education sectors.
Strengths
Business Model: Funnelback offers the most flexibility in terms of enabling combinations of components for deployment in different hosting environments. Government and military clients have helped Funnelback refine a rich deployment topology across private and public clouds.
Personalization (Product or Service): Funnelback offers the strongest personalization capabilities in this Magic Quadrant, with comprehensive support for both implicit and explicit context, in addition to proactive suggestions.
Geographic Strategy: Funnelback’s customer base is evenly distributed across Asia/Pacific, EMEA and North America. Likewise, its offices are split across these three regions, with the majority in the largest region, Asia/Pacific. Funnelback’s largest gains in terms of new customers have been in Asia/Pacific.
Cautions
Marketing Execution: Funnelback appears infrequently in the shortlists of buyers that are shown to Gartner. This partly results from its narrowed industry strategy — the emphasis on higher education and government means that potential customers outside these sectors may not see its solution as fit for their vertical.
Operations: Funnelback is one of the smallest companies in this market in terms of number of employees. With the majority of these employees being customer-facing, less time is spent on core platform development and operational excellence.
Business Model: Of the vendors in this Magic Quadrant, Funnelback is utilized across the fewest functional domains within organizations. It therefore faces a challenge to “land and expand” beyond the use cases for which it was initially purchased.
Google is a Challenger in this Magic Quadrant. Its product is Google Cloud Search, which was launched in July 2018. The product’s principal use case is to support internal (intranet) search.
Google is a publicly traded company. Its operations are geographically dispersed — its headquarters are in Mountain View, California, U.S., and it has 84 more offices worldwide. Its partners, of which there are around 17,000, are also located around the world. Customers come from a broad range of industries, but especially communications, media and services, banking and securities, and manufacturing and natural resources.
Google plans to keep expanding the use of Google Cloud Search within its Google Workspace offering in order to bolster its cloud office suite. Furthermore, it is likely to create synergy across products by integrating more deeply with related AI offerings such as Document AI and Google Assistant.
Strengths
Marketing Execution: Google benefits from enviable mind share, built on a strong reputation in this domain, and has experience to match. Google is one of the vendors most considered by customers before deciding to procure a particular insight engine.
Offering (Product) Strategy: Google demonstrates a clear vision for Google Cloud Search, both as a foundational insight engine supporting search within a cloud office and in the context of specific domains and situations via in-application or custom-made application search capabilities.
Customer Experience: Customers of Google praise it for postdeployment agility — the ability to put its product to many different uses, once deployed and operational.
Cautions
Vertical/Industry Strategy: Google Cloud Search is positioned to serve all industries, rather than serve as a platform for the development of solutions for specific industries, functional domains and situations. Although the product is capable of application to domain and situational use cases, the expertise for doing so lies with Google’s partners, rather than Google itself.
Market Understanding: Google’s understanding of this market, both in terms of the buyers of insight engines and especially of competitors and adjacent markets, lags behind that of other vendors, given Google’s relatively narrow focus on internal (intranet) search.
Innovation: Although Google Cloud Search is a strong product, it is hosted by Google with tight integration with Google Workspace. Integration with third-party applications for the delivery of insight is limited, especially with respect to prebuilt integration. Furthermore, the ingestion of content and data via connectors is too dependent on third-party providers.
IBM
IBM is a Leader in this Magic Quadrant. Its product is Watson Discovery. The product’s principal uses are to provide a platform on which insight applications can be developed, and to facilitate the delivery of insight to other applications making up a digital workplace.
IBM is a publicly traded company. Its operations are geographically dispersed, with a headquarters in Armonk, New York, U.S., and around 200 more offices around the world. Its partners, of which there are about 65,000, are located worldwide. Its customers come from a broad range of industries, but especially IT services and software, insurance, and banking.
IBM plans to continue to focus on connecting Watson Discovery to its wider portfolio in order to facilitate natural language applications. For example, it plans to integrate more tightly Watson Speech to Text, Watson Assistant, Watson Discovery and Watson Media.
Strengths
Offering (Product) Strategy: IBM’s search and conversational products share an information architecture, which makes their integration among the tightest shown by vendors in this Magic Quadrant. This is evidence of a stronger, broader vision for NLTs.
Product or Service: IBM has made major improvements to its table extraction capabilities with Smart Document Understanding. The use of human-in-the-loop annotation to support identification, management and enrichment of tabular data and the creation of custom models enables tables to become a more integral part of insights.
Market Understanding/Strategy: IBM caters to one of the highest numbers of well-rounded use cases in this market, across various functional domains within organizations.
Cautions
Vertical/Industry Strategy: IBM lacks the comprehensive industry accelerator offerings and templates that others in this market provide. As a result, buyers may find they require more postdeployment and training work to tune its insight engine to their business.
Sales Strategy: Accessing relevant partners for specific IBM products — in this case, Watson Discovery — is a challenge. Although IBM maintains a presence in other marketplaces, such as AWS Marketplace, the characteristics of its partner network, together with the need to understand the wider product portfolio, make it challenging to find the right path to a solution.
Ability to include key data sources (Product or Service): The number of connectors for the Watson Discovery service has increased, but remains below average for the market. In addition, approximately half these connectors are optional and entail additional charges — in contrast to other competitors. Beyond IBM’s own connectors, only one is available from third-party providers.
IHS Markit
IHS Markit is a Niche Player in this Magic Quadrant. Its Goldfire product focuses on the creation of insight applications for technical employees who require insights drawn from complex technical sources both within and external to their enterprise.
IHS Markit is a publicly traded company. Its operations are geographically dispersed, with a headquarters in London, U.K., and 94 more offices around the world. Its partners, of which there are about 930, are located worldwide. In addition to reselling, the majority of its partners offer professional services. Its customers come from a broad range of industries, but especially transportation and manufacturing and natural resources.
IHS Markit’s Goldfire product now has its own branding and web presence to increase its visibility. In 2019, IHS Markit acquired Novation Analytics, a purchase that is likely to deepen its offerings in the automotive sector to support strategic planning and regulatory and competitive analysis.
Strengths
Ability to include key data sources (Product or Service): Goldfire’s ability to connect to and index a client’s various sources of data is strong. This reflects IHS Markit’s approach to customized development of connectors to support its clients.
Operations: IHS Markit’s organizational structure positions its staff to provide the right balance of customer-facing services and product-facing development and support. This is further evidenced by customers’ experience of the vendor.
Customer Experience: Reviewers on Gartner’s Peer Insights platform rate IHS Markit highest in this market across a range of measures, such as quality of product and professional services and agility after deployment.
Cautions
Marketing Execution: Although Goldfire commands a strong position in public search, its limited web and social media presence diminishes IHS Markit’s ability to execute its marketing strategy. Despite the vendor’s large size, our analysis of vendors considered by buyers in this market indicates that IHS Markit commands limited mind share.
Multiple languages (Product or Service): IHS Markit supports a limited set of languages, compared with other vendors in this Magic Quadrant, although it does this at a semantic level and in terms of documentation and user interface, as well as processing.
Sales Strategy: Without professional services partners, or the capability to work independently of the vendor, IHS Market’s clients have limited choices in terms of deployment strategy. IHS Markit always works with its customers directly to deploy and implement its product.
IntraFind
IntraFind is a Challenger in this Magic Quadrant. Its iFinder product is broadly focused on digital workplace search knowledge management, metadata enrichment, and providing a platform for the creation of insight applications.
Intrafind is a privately owned company. Its operations are mostly in EMEA. It has headquarters in Munich, Germany, and two more offices in Bonn, Germany, and New York, U.S. Its 46 partners are primarily located in Germany, with a minority providing professional services, in addition to their reselling activities. Its customers come from a narrow range of industries, especially the automotive, natural resources and materials, and national and international government sectors. Most of its customers are based in EMEA.
IntraFind plans to further its deep document intelligence capabilities, especially in legal technology, with a focus on personalization and user touchpoint innovation. It also plans to improve development times by upgrading its connector framework to enable simpler and more rapid connector development. It distinguishes itself from the technology heavyweights by customizing and personalizing solutions for heterogeneous IT environments.
Strengths
Business Model: IntraFind’s strong business model combines an excellent range of options for deployment with opportunities to prove the technology inside an organization. In addition, IntraFind has one of the simplest pricing models in this market, which enables existing and prospective customers to forecast cost and compare prices more easily.
Overall Viability: Gartner’s methodology for scoring the overall financial viability of vendors rates IntraFind as “Positive.” IntraFind is one of two privately owned vendors that stand out in this market with respect to this criterion.
Customer Experience: Although scores are not consistently high in all areas, reviewers on Gartner’s Peer Insights platform rate the quality of IntraFind’s product and professional services highly.
Cautions
Marketing Strategy: Despite having a good understanding of this market, with clarity about use cases and buyer personas, IntraFind lacks a clear and consistent value proposition. This shortcoming is compounded by the least mature marketing plans of any vendor in this Magic Quadrant, which diminishes IntraFind’s Ability to Execute.
Sales Strategy: A tendency to use localized partners — primarily in Germany, Austria and Switzerland — diminishes IntraFind’s channel strategy. This is especially evident in the lack of partners across its fractured web presence. With only one in five of its partners being outside Europe, customers in other regions need to ensure the vendor has partners that can serve them, or that it can do so itself, despite geographical constraints.
Offering (Product) Strategy: Although it offers a separate product for legal professionals (Contract Analyzer), IntraFind provides no variants of its product for specific industry or functional domains. In addition to this, a lack of clarity about its roadmap makes IntraFind’s vision for iFinder challenging to discern.
Lucidworks
Lucidworks is a Visionary in this Magic Quadrant. Its product is Lucidworks Fusion. Along with Fusion, the company offers add-on applications called Smart Answers (conversational middleware) and Predictive Merchandiser (for digital commerce experience optimization). Fusion’s principal uses are to support discovery of information and data in digital workplaces, and to support digital commerce via customer-facing websites.
Lucidworks is a privately owned company. Its operations are geographically dispersed, with headquarters in San Francisco, California, U.S., and five more offices in Asia/Pacific, EMEA and North America. Its partners, of which there are around 138, are geographically dispersed. The majority provide professional services or development of IP, in addition to their reselling activities. Lucidworks’ customers come from a broad range of industries, but especially the IT and software services, health insurance, national and international government, and banking sectors. Most of its customers are based in North America.
In late 2020, Lucidworks drew on its search and AI capabilities to bring Connected Experience Cloud to market. This highlights its 2021 focus on end-to-end journeys and turning insights into actions. Taking charge of end-to-end experiences and providing explainable AI provides differentiation for this vendor.
Strengths
Geographic Strategy: With a geographically widespread customer base and offices and partners in many locations, Lucidworks’ geographic strategy stands out among vendors in this market. It is comparable, if not superior, to those of larger vendors.
Market Understanding: Lucidworks’ understanding of this market is strong, demonstrating a solid knowledge of its competitors’ strengths and weaknesses. In addition, it demonstrates a keen sense of markets adjacent to the insight engine market.
Ability to analyze result sets (Product or Service): Fusion’s ability to enrich data contributes to its strength in analyzing result sets. Lucidworks’ product supports a broad range of use cases across industries and functions, confirming its contribution not just to search but also to the creation of new information from data using analytical capabilities.
Cautions
Business Model: Lucidworks has recently changed the pricing model for its product, from compute-based to usage-based. In its present form, it is among the most complex pricing models in this market, with four factors determining the price: product tier, usage category, hosting and usage (objects indexed plus queries run). Complex pricing models made it harder for customers to forecast costs and compare vendors during review and procurement cycles.
Marketing Execution: Despite its strong association with Apache Solr, on which Fusion is built and to which many Lucidworks staff contribute, Lucidworks lacks the mind share associated with Solr and its alternative, Elasticsearch.
Security (Product or Service): Lucidworks’ score for security is diminished by the absence of third-party attestations to validate its claims about the security of its product — in contrast to most of the vendors in this Magic Quadrant. LucidWorks acknowledges this and reports that it is pursuing certification.
Micro Focus
Micro Focus is a Niche Player in this Magic Quadrant. Its IDOL product focuses on deep analysis of content, especially rich media, in order to extract data in support of analytics and insight applications for compliance, security and knowledge management.
Micro Focus is a publicly traded company. Its operations are geographically dispersed, with a headquarters in Newbury, U.K., and 105 more offices around the world. Its partners, of which there are approximately 6,500, are also dispersed worldwide. A minority of its partners provide professional services, in addition to their reselling activities. Its customers come from a range of industries, but especially the government, consumer nondurable goods, publishing and advertising, banking and securities, and IT services and software sectors. The majority of its clients are based in EMEA and North America.
Micro Focus continues to develop its mature product. Incremental improvements are led by customer demand — for example, to extend IDOL’s deployments from on-premises to limited hybrid deployments with respect to connectors and user-facing applications built on IDOL.
Strengths
Sales Strategy: IDOL’s use by many well-known global system integrators (GSIs) underpins a successful sales strategy. Micro Focus’ strategy balances direct and indirect sources of revenue.
Vertical/Industry Strategy: With its broad range of products, some of which embed IDOL as a constituent part, Micro Focus can reach a broad range of industries through its customers, with solutions adapted by its strong partner network.
Ability to analyze result sets (Product or Service): IDOL can draw data from many and varied sources of content, and support users with interactive analysis tools for the generation of insights or the development of insight applications.
Cautions
Business Model: Micro Focus’ deployment options for IDOL are limited to on-premises and private cloud, with the burden of responsibility for infrastructure and application management resting with the client. In addition, IDOL’s pricing model is relatively complex, and the total cost of ownership is at the higher end of the scale for products in this market.
Market Understanding and Marketing Strategy: Micro Focus’ understanding of its buyer personas is limited, compared with other vendors in this market. This shortcoming, combined with a value proposition that lacks uniqueness, undermines its capability to market its product to buyers.
Customer Experience: Reviewers on Gartner’s Peer Insights platform reveal lower levels of satisfaction with Micro Focus than with other vendors in terms of product, professional services and agility after deployment, but especially across all measures taken together.
Microsoft
Microsoft is a Challenger in this Magic Quadrant. Its Microsoft Search product focuses on Microsoft 365. It uses Microsoft’s own touchpoints, either those dedicated to Microsoft Search itself or those integral to other Microsoft applications within Microsoft 365.
Microsoft is a publicly traded company. Its operations are geographically dispersed, with a headquarters in Redmond, Washington, U.S., and 231 more offices around the world. Its partners, of which there are around 65,000, are similarly dispersed worldwide. Its customers come from a broad range of industries, but especially national and international government, banking, IT services and software, telecommunications, and insurance.
Microsoft Search will remain largely insular to Microsoft 365, but Microsoft has begun to broaden and deepen its integration with content services products, as well as expand its functionality to adapt search to the needs of users across enterprises. For example, Microsoft plans to include support for conversational search, including Q&A, as well as strong customization of the experiences provided to users.
Strengths
Offering (Product) Strategy: Microsoft is building a comprehensive set of information applications with tight integration across Microsoft Search, Microsoft Power Apps, Microsoft Bot Framework, Microsoft Graph and products derived from Project Cortex (such as Microsoft Syntex). In this way, it can derive insights from a rich corpus of content and data, as well as present insights through a variety of applications across Microsoft 365.
Marketing Execution: Among prospective buyers, Microsoft dominates with respect to their consideration of other vendors. For many — those with Microsoft 365 — Microsoft Search is their foundational search solution, with the key question being whether domain and situational uses can be addressed. Although awareness of Microsoft Search is still growing, Microsoft is among the few vendors providing thought leadership in this market.
Operations: With a large and strong cohort of staff dedicated to search functionality, Microsoft is well-placed to apply expertise directly to the development of Microsoft Search.
Cautions
Sales Strategy: Although Microsoft has an extensive partner network, it is challenging to identify partners for Microsoft Search that can provide specialist services in customers’ locations. Given the specialist nature of search, this obstructs Microsoft 365 customers who, with Microsoft Search by default, often end up relying on their own in-house capabilities and capacity, or that of their Microsoft 365 partner.
Vertical/Industry Strategy: Positioned as an integral part of Microsoft 365, Microsoft Search has no variants available to serve a particular industry, function or application portfolio. Given the challenge of finding the right partner, Microsoft’s reliance on Microsoft Graph requires clients to await new releases or enhancements (such as those arising from Project Cortex) in order to develop the adaptations they need.
Business Model: Although Microsoft offers the best pricing model, as well as drivers that outweigh inhibitors of adoption, the limited choices for hybrid deployment scenarios diminish its appeal. Customers wishing to accommodate on-premises data sources must await the release of third-party connectors, or deploy a separate on-premises instance of SharePoint Search, to implement hybrid indexing.
Mindbreeze
Mindbreeze is a Leader in this Magic Quadrant. Its product is Mindbreeze InSpire. The product’s principal use cases are enterprise search, employee portals, intranet search and knowledge management, customer service maintenance support, and search-driven business intelligence (BI).
Mindbreeze is a subsidiary of its publicly traded owner, Fabasoft. Its operations are mostly in EMEA, with a headquarters in Linz, Austria, and a further seven offices in EMEA and North America. Its partners, of which there are 139, are dispersed worldwide. The majority provide professional services, in addition to their reselling activities. Its customers come from a broad range of industries, but especially healthcare provision (hospitals), government, telecommunications and banking. Most of its customers are based in EMEA or North America.
Mindbreeze continues to develop its indirect channels, which include value-added resellers, with the introduction of a partnership program for independent software vendors. This enables its product to be integrated into third-party products and services through OEM partnerships.
Strengths
Product or Service: Mindbreeze InSpire demonstrates strength across a range of product features, such as inclusion of key data sources, architecture and deployment model, and data enrichment. InSpire offers the widest range of connectors to sources of data and content, the greatest flexibility in deployment options, and the strongest pipeline for extracting data from sources of content and data.
Innovation: Mindbreeze scores strongly for innovation, due to its ability to use AI technologies (especially throughout the components comprising its products), participation in digital ecosystems, incorporation of third-party technologies, and innovation with both customers and partners.
Customer Experience: Reviewers on Gartner’s Peer Insights platform rate Mindbreeze highest for their overall experience with the vendor. They are especially satisfied with the quality of Mindbreeze’s product and with the professional services provided in relation to it.
Cautions
Sales Strategy: Although Mindbreeze has a relatively large partner network for this market, access to these partners is diminished by a basic partner catalog. Few of the partners represented are GSIs, and there is a lack of clarity about how partners are categorized (for example, resale versus service, local versus global, technical versus business). Although Mindbreeze provides its own closed marketplace of components built on its platform by customers, it has no presence on third-party marketplaces.
Offering (Product) Strategy: No variants of Mindbreeze InSpire are offered to provide customers a starting point adapted to their industry, function or application portfolio.
Marketing Execution: For a vendor consistently placed in the Leaders quadrant, Mindbreeze is relatively lacking in mind share and visibility. Furthermore, Mindbreeze has not provided thought leadership for the market as a whole, but instead relied on larger vendors to set the agenda.
Sinequa
Sinequa is a Leader in this Magic Quadrant. Its product is Sinequa ES. The product’s principal uses are for enterprise search, unified enterprise content portals, expert finding, 360-degree (entity-centric) information views, market intelligence, news/trend analysis, asset management, portfolio management, customer service, information protection and data privacy.
Sinequa is a privately owned company. Its operations are mostly in EMEA, with a headquarters in Paris, France, and eight more offices elsewhere in EMEA and North America. Its 41 partners are located primarily in EMEA; a minority provide professional services, in addition to their reselling activities. Its customers come from a range of industries, but especially manufacturing and natural resources, government, and banking and securities. The majority of its customers are based in EMEA.
Sinequa continues to deepen its use of ML throughout its product. It plans to introduce a connector to portions of Microsoft Graph, specifically for content within Microsoft SharePoint and OneNote.
Strengths
Market Understanding: Sinequa’s understanding of this market is strong, demonstrating clarity across each of this market’s four principal use cases, as well as many others. Buyer personas are not only clearly identified but valid for this market, and their priorities are clearly understood. But it is in its awareness of competitors and adjacent markets that Sinequa really excels — it understands their places in the market and demonstrates a keen sense of where opportunities and risks lie.
Innovation: Sinequa uses AI technologies throughout the pipeline of its product (from indexing to querying). It does so while participating in a broad ecosystem of third parties, in order to blend first-party, third-party and open-source components.
Overall Viability: Gartner’s methodology for scoring the overall financial viability of vendors rates Sinequa as “Positive.” Sinequa is one of only two privately owned vendors that stand out in this market with respect to this criterion.
Cautions
Offering (Product) Strategy: Although Sinequa has a strong vision for its product, the offering falls short overall in terms of prepackaged variants tailored to industry, function or experience. It has yet to differentiate itself clearly in this market.
Marketing Execution: In common with some other vendors, Sinequa lacks significant presence beyond its own website. It has limited mind share among prospective buyers of insight engines, judging by Gartner’s knowledge of their consideration of vendors, despite its long-standing position as a Leader.
Security (Product or Service): Our methodology for assessing the security of products in this market identifies Sinequa as not providing clear support for compliance requirements and third-party attestations.
Squirro
Squirro is a Visionary and a new entrant in this Magic Quadrant. Its Squirro Insights Engine product can fulfill use cases across an enterprise, with a focus on marketing and sales, IT and operations.
Squirro is a privately owned company. Its operations are mostly in EMEA, with a headquarters in Zurich, Switzerland, and four more offices in EMEA, Asia/Pacific and North America. Its 35 partners are dispersed around the world, and most provide professional services, in addition to their reselling activities; a minority develop IP. Its customers come from a narrow range of industries, especially banking, IT services and software, and insurance. The majority of its customers are based in EMEA.
Given its emphasis on delivering actionable insights, Squirro plans to develop its product’s capability to become interactive and proactive through the introduction of user notifications and conversational AI.
Strengths
Sales Strategy: Squirro uses a range of indirect channels to reach prospective customers and generate revenue. These include both global and local system integrators and service providers (such as Wipro and Kudaw) and marketplaces (such as the Microsoft Azure Marketplace). Revenue is well-balanced between direct and indirect channels, and between indirect services and reselling.
Vertical/Industry Strategy: Squirro offers a range of product variants across industry and functional domains, and enables tailored solutions — a distinctive feature in this market. Variants are available for the banking and finance, insurance, and manufacturing sectors. Although the number of industries supported is below average for this market, Squirro demonstrates a healthy distribution of both customers and staff across the industries it does serve. This provides a model and a basis for growth as it expands into new industries.
Marketing Strategy: Squirro’s marketing strategy is strong, with its differentiated positioning for the delivery of actionable insights to key roles being clearly and consistently articulated. It also has strong marketing plans to reach likely future customers.
Cautions
Sales Execution/Pricing: The total cost of ownership is high, although this is not uncommon for this market. In addition, Squirro’s pricing model is comparatively complex, with many factors contributing to the total price. This is reflected in Squirro’s customer satisfaction, with diminished ratings for contract and price negotiation.
Evaluation and tuning of relevance (Product or Service): Other vendors offer a richer range of features to facilitate the tuning of relevance. In addition, Squirro’s approach emphasizes manual tuning by administrators, rather than automated tuning facilitated by subject matter experts.
Marketing Execution: Despite a strong marketing strategy, Squirro has yet to develop much of a presence beyond its own marketing channels, or offer thought leadership in this market. Gartner Peer Insights data indicates that, of the vendors in this Magic Quadrant, Squirro has the lowest level of visibility to prospective customers of insight engines.
Vendors Added and Dropped
We review and adjust our inclusion criteria for Magic Quadrants as markets change. As a result of these adjustments, the mix of vendors in any Magic Quadrant may change over time. A vendor's appearance in a Magic Quadrant one year and not the next does not necessarily indicate that we have changed our opinion of that vendor. It may be a reflection of a change in the market and, therefore, changed evaluation criteria, or of a change of focus by that vendor.
We review and adjust our inclusion criteria for Magic Quadrants as markets change. As a result of these adjustments, the mix of vendors in any Magic Quadrant may change over time. A vendor’s appearance in a Magic Quadrant one year and not the next does not necessarily indicate that we have changed our opinion of that vendor. It may be a reflection of a change in the market and, therefore, of changed evaluation criteria, or of a change of focus by that vendor.
Added
Elastic
Squirro
Dropped
Attivio: This vendor’s IP, core technology and a selection of key staff have been acquired by ServiceNow. Attivio continues to serve customers it acquired previously, but no longer competes meaningfully in this market.
Dassault Systèmes: A design and engineering specialist offering a wide array of product development services across manufacturing and 3D products and environments. Although Dassault Systèmes offers a comprehensive set of solutions for industrial applications, the applicability of its insight engine is limited for other purposes and beyond its other products.
Inclusion and Exclusion Criteria
To qualify for inclusion in this Magic Quadrant, vendors needed to:
Sell a product that:
Met the market definition: Insight engines are systems that apply relevancy methods to describe, discover, organize, and analyze content and data. This approach allows for existing or synthesized information to be delivered proactively or interactively in the context of digital workers, customers or other constituents at timely business moments.
Was available as a separate, independent software product or as part of a cloud office platform intended to support knowledge workers in all roles.
Used connectors to access and gather content/data of varying types from multiple repositories other than those sold by the vendor.
Created an index by processing gathered content/data, and made this available via query through multiple touchpoints (for humans) and integrations (for machines).
Served two of the four principal use cases for products in this market, namely internal (intranet) search and insight applications.
Had been generally available for at least a year, as of midnight, U.S. Eastern Daylight Time on 1 April 2020.
Had technical capabilities, features and functionality present within the product or supported for download prior to midnight, U.S. Eastern Daylight Time on 1 April 2020.
Earn revenue, directly attributable to their product, of more than $8 million in 2019, or at least $6 million with a three-year compound annual growth rate (starting in 2017) of 20% or more.
Have an installed base for their product comprising:
Customers in two or more major geographic regions, including North America or Europe, the Middle East and Africa (EMEA).
Customers in three or more vertical/industry categories.
Honorable Mentions
Amazon Web Services: This vendor brought its fully managed enterprise search offering, Amazon Kendra, to market in 2020, but too late for inclusion in this Magic Quadrant.
SearchBlox: This vendor offers an insight engine, built on Elasticsearch, that did not fully meet the inclusion criteria for this Magic Quadrant.
Evaluation Criteria
Gartner analysts evaluate technology providers on many factors. These include the quality and efficacy of the processes, systems and methods that enable performance to be competitive, efficient and effective. Ultimately, technology providers are judged on their ability to capitalize on their vision and their success in doing so.
Ability to Execute
Ability to Execute measures a vendor’s insight engine product or service, overall viability, and ability to develop, market, sell and support its product or service. Criteria included:
Product or Service: Critical capabilities, namely the ability to include key data sources; the ability to analyze result sets; architecture and deployment model; support for data enrichment; delivery of results to various touchpoints; evaluation and tuning of relevance; security; ease of use; support for multiple languages; personalization; and query input flexibility.
Overall Viability: A vendor’s financial viability, the growth or decline of its customer base, and the size of its business.
Sales Execution/Pricing: Pricing relative to competitors, sales performance, and customer satisfaction with negotiation and pricing.
Marketing Execution: Awareness of a vendor’s brand among prospective buyers, digital presence beyond a vendor’s website, and thought leadership.
Customer Experience: Customer ratings of agility after deployment, the vendor’s product or service, and professional services.
Operations: Distribution of staff across functional domains, efficacy of services and organizational structuring.
Due to the exceptional circumstances of 2020 arising from the COVID-19 pandemic, we did not rate Market Responsiveness/Record. Instead, we plan to revisit this criterion in the next edition of this Magic Quadrant.
Table 1 shows the weighting of each criterion.
Table 1: Ability to Execute Evaluation Criteria
Evaluation Criteria | Weighting |
Product or Service | High |
Overall viability | Medium |
Sales Execution/Pricing | Medium |
Market Responsiveness/Record | Not Rated |
Marketing Execution | Low |
Customer Experience | High |
Operations | Medium |
Source: Gartner (March 2021)
Completeness of Vision
Completeness of Vision measures how well a vendor understands the insight engine market and steers its product, marketing, sales, product, and contextualization in terms of industries and geographies, and how it aligns its business model. Criteria included:
Market Understanding: Awareness of, and clarity about, use cases, buyer personas and competitors.
Marketing Strategy: Marketing plans, value proposition and messaging.
Sales Strategy: Channel strategies, partnering and supply to customers.
Offering (Product) Strategy: Product vision, differentiation and prepackaged capabilities.
Business Model: Pricing model, deployment model, and opportunities to “land and expand.”
Vertical/Industry Strategy: Product variants, plus distribution of customers and expertise across industry domains.
Innovation: Utilization of AI, participation in a wider digital ecosystem of third-party technologies, and co-innovation with customers and partners.
Geographic Strategy: International presence of offices, partners and customers.
Table 2 shows the weighting of each criterion.
Table 2: Completeness of Vision Evaluation Criteria
Evaluation Criteria | Weighting |
Market Understanding | High |
Marketing Strategy | Low |
Sales Strategy | Low |
Offering (Product) Strategy | High |
Business Model | Low |
Vertical/Industry Strategy | Medium |
Innovation | Medium |
Geographic Strategy | Low |
Source: Gartner (March 2021)
Quadrant Descriptions
Leaders
Leaders demonstrate a strong understanding of the insight engine market, along with marketing plans that differentiate and communicate value to reach buyers across a range of use cases. They have the sales or geographic strategy to exploit their marketing effectively. Offering products that demonstrate strength across the broadest range of critical capabilities, they have strong overall viability, sales execution and operations. Customers praise their experiences of Leaders’ products or services, and of the vendors themselves. However, potential customers should note that a Leader is not always the best choice. A smaller, more focused vendor could potentially provide excellent support for, and commitment to, individual needs.
Challengers
Challengers have strong business models that support comprehensible and competitive pricing models, and offer good opportunities to expand usage of their products. They have a strong geographic presence. Their products or services demonstrate strength across a range of critical capabilities (although not as many as Leaders). Challengers also have strong overall viability, sales execution and operations. Although their market understanding and strategy falls short of that of Leaders, they demonstrate prowess in the execution of their marketing, delivering both presence and awareness among potential buyers. Customers praise their experiences of Challengers’ products and services, and of the vendors themselves. Challengers are usually a good choice for large, horizontal enterprise initiatives. They should be assessed alongside Leaders for such initiatives.
Visionaries
Visionaries combine their understanding of the insight engine market with strength in innovation. They align well with industry needs and have the sales strategy needed to fulfill them. Visionaries offer products that demonstrate competence across a range of critical capabilities, with particular strengths in some key areas. However, they lack the level of overall viability that Leaders possess, and they tend to lag in terms of marketing execution, which results in diminished visibility and brand awareness. Visionaries are suitable for organizations looking to modernize and transform themselves by tackling familiar problems in new ways. Prospective customers should, however, check whether these vendors can scale their services to meet the demands of large international projects with broad horizontal use-case requirements.
Niche Players
Niche Players apply their strength in industry strategy to target particular industries, functional domains, use cases or geographical regions. Their geographic strategy limits their international reach. They offer products that demonstrate competence across a range of critical capabilities, with particular strengths in one or a few of these. Niche Players lack the level of overall viability that Leaders possess, and tend to lag in terms of marketing execution, which results in diminished visibility and brand awareness. A Niche Player could potentially provide better capability for a given use case than a more general vendor categorized as a Leader.
Context
This Magic Quadrant is intended to help application leaders make vendor and product selection decisions in the market for insight engines. In this market, they will find vendors offering products and services to create solutions that provide an adaptable query engine for an enterprise’s full range of content and data, as well as external sources.
Insight engines should never be treated as discrete, insular applications. Rather, they tap into, enhance, and extend a wide variety of other data types, sources and systems. Thus, they are integral to an organization’s digital ecosystem, which is complex, extensive and interconnected. Additionally, their use of natural language, in terms of what is indexed and how it is queried, places them in the wider context of an organization’s use of NLTs. Consequently, deployment times average around half a year, although some take only a couple of months and others more than a year.
Organizations looking to procure an insight engine should first consider which, if any, engines they currently deploy. They should then decide whether to introduce a foundational solution to serve all employees and their myriad use cases, or just to add a service to an incumbent foundational solution and thus enable development of domain and situational applications for specific use cases.
This Magic Quadrant represents a snapshot of the market. Year-over-year comparisons should be avoided. It will help you select an insight engine, but do not use it as your only aid. Also consult the companion Critical Capabilities for Insight Engines, which will help you identify product differentiation and use-case alignment.
Your final selection criteria must reflect your organization’s functional and technical requirements and business objectives. Do not, for example, select a Leader or reject a Niche Player simply because it is categorized as such. Assess any vendor that meets your essential requirements — a vendor in any one of the four quadrants could be the best choice for your needs.
Market Overview
For many organizations, their subscription to Microsoft 365 or Google Workspace includes an insight engine, which serves as a foundational solution for all their employees. However, limitations on the inclusion of third-party data sources, customization throughout the index and query pipelines, or control of configuration should prompt consideration of these vendors’ other products and services, and those of other vendors in this Magic Quadrant. This is especially the case when looking to address domain or situational use cases, but might also apply to substitution of the foundational solution to which all employees are steered.
As businesses evolve to become digital and to generate more structured and unstructured content, the need for insight engine technology to surface relevant facts, content and knowledge to stakeholders is critical. Vendors in this market have mature solutions and offer cost-effective and systemic approaches to improving the development and consumption of knowledge across an enterprise. From a value for money standpoint, insight engines offer flexibility and broad applicability when it comes to getting and pushing knowledge to the broadest set of customers and employees — in contrast to, for example, conversational technologies and intelligent document processing solutions.
Key trends include:
Natural language and conversational interfaces: In contrast to the narrow and often custom-made development of chatbot and Q&A systems, insight engines typically span an entire enterprise. They are able to surface, via typed natural language (and increasingly speech), facts and knowledge from a variety of areas, such as CRM, external social data, marketing, IT service management, HR and sales. One aspect of differentiation is the use of connectors or prebuilt integrations to access both new data sources and platform user interfaces and workflows. In 2020, we saw evolution in the AI techniques and modalities supported by insight engines, which now often offer a broader range of natural-language-related technologies, such as conversational AI and elements of intelligent document processing. Beyond search, insight engines use a range of NLTs to extract and model data for indexing, and to comprehend users’ intentions when querying an index. While some insight engines use, and are limited to, their own underlying AI, others engage an array of third-party technologies, the list of which is growing. Consequently, some vendors can match questions to the best-fit answers in the form of snippets of documents. Few, however, support true conversation with natural language generation or maintenance of state between utterances. We expect 2021 to be a transformational year for NLTs and that insight engines could play a major role in their evolution. However, over half the vendors in this Magic Quadrant seem not to be planning for the convergence of NLTs.
Semantic integrity: Insight engines create new indexes by crawling, mining and indexing both structured and unstructured content in both internal and external data sources to ensure that a broad set of information is easily discoverable. Vendors in this sector extend the reach of their content-indexing capabilities to rich media (either natively or via partnership) by using ML capabilities such as computer vision, optical character recognition and speech-to-text. The resulting indexes are often complemented by semantic language and context models, such as ontologies and graphs, to ensure that similar concepts and objects represented by different schemas can be consistently modeled. In contrast to search engines that provide links to original source materials such as documents and videos, insight engines can also provide contextual information about the fact or entity in question. For example, rather than simply link to HR employee profiles, an insight engine can present a richer set of information, such as employees’ social connections, upcoming meetings and outstanding IT support tickets.
Touchpoints and integrations: Delivery of insights is no longer restricted to separate touchpoints that draw users’ attention away from their main tools. Increasingly, vendors are creating custom touchpoints to provide prebuilt integration with the tools employees use to get work done. This includes CRM, ERP, IT service management and other categories of tools, as well as the New Work Hub. This is in addition to customized touchpoints specific to certain clients and their needs in domain and situational scenarios. Flexible presentation of results is a key capability of insight engines.
Persistence of open-source software: Customers interested in insight engines often shortlist Elastic’s Elasticsearch and Apache’s Solr technology. But neither Elasticsearch nor Solr are true insight engines by themselves — extensive development is required for them to meet the definition of an insight engine used in this Magic Quadrant. However, their consideration provides validation of the underlying technology and the communities that develop it, as well as recognition that the effective delivery of insight goes beyond what many organizations can realistically deliver and support themselves. Consequently, a number of vendors have built their insight engines on top of Elasticsearch and Solr. This year, the inclusion of Elastic — due to its product built on Elasticsearch — expands the number of vendors, adding to Lucidworks (which uses Solr) and IntraFind (which uses Elasticsearch).
Innovation: In this market, innovation is partly facilitated by capabilities derived from other products, either those of the main vendor or third parties. In many cases, the components — or at least the techniques used — are also available to competitors or to vendors in other markets that offer content-centric applications such as chatbots or intelligent document processing tools. Our engagement with a range of vendors and clients over the past year reveals that capabilities similar to those of insight engines are emerging in many markets. Consequently, the gap between the insight engine market and other markets (whether or not explicitly recognized by Gartner as distinct markets) is closing. Both greater confusion and wider choice are likely to arise as new vendors compete directly in this market or offer partially overlapping capabilities.
Evaluation Criteria Definitions
Ability to Execute
Product/Service: Core goods and services offered by the vendor for the defined market. This includes current product/service capabilities, quality, feature sets, skills and so on, whether offered natively or through OEM agreements/partnerships as defined in the market definition and detailed in the subcriteria.
Overall Viability: Viability includes an assessment of the overall organization's financial health, the financial and practical success of the business unit, and the likelihood that the individual business unit will continue investing in the product, will continue offering the product and will advance the state of the art within the organization's portfolio of products.
Sales Execution/Pricing: The vendor's capabilities in all presales activities and the structure that supports them. This includes deal management, pricing and negotiation, presales support, and the overall effectiveness of the sales channel.
Market Responsiveness/Record: Ability to respond, change direction, be flexible and achieve competitive success as opportunities develop, competitors act, customer needs evolve and market dynamics change. This criterion also considers the vendor's history of responsiveness.
Marketing Execution: The clarity, quality, creativity and efficacy of programs designed to deliver the organization's message to influence the market, promote the brand and business, increase awareness of the products, and establish a positive identification with the product/brand and organization in the minds of buyers. This "mind share" can be driven by a combination of publicity, promotional initiatives, thought leadership, word of mouth and sales activities.
Customer Experience: Relationships, products and services/programs that enable clients to be successful with the products evaluated. Specifically, this includes the ways customers receive technical support or account support. This can also include ancillary tools, customer support programs (and the quality thereof), availability of user groups, service-level agreements and so on.
Operations: The ability of the organization to meet its goals and commitments. Factors include the quality of the organizational structure, including skills, experiences, programs, systems and other vehicles that enable the organization to operate effectively and efficiently on an ongoing basis.
Completeness of Vision
Market Understanding: Ability of the vendor to understand buyers' wants and needs and to translate those into products and services. Vendors that show the highest degree of vision listen to and understand buyers' wants and needs and can shape or enhance those with their added vision.
Marketing Strategy: A clear, differentiated set of messages consistently communicated throughout the organization and externalized through the website, advertising, customer programs and positioning statements.
Sales Strategy: The strategy for selling products that uses the appropriate network of direct and indirect sales, marketing, service, and communication affiliates that extend the scope and depth of market reach, skills, expertise, technologies, services and the customer base.
Offering (Product) Strategy: The vendor's approach to product development and delivery that emphasizes differentiation, functionality, methodology and feature sets as they map to current and future requirements.
Business Model: The soundness and logic of the vendor's underlying business proposition.
Vertical/Industry Strategy: The vendor's strategy to direct resources, skills and offerings to meet the specific needs of individual market segments, including vertical markets.
Innovation: Direct, related, complementary and synergistic layouts of resources, expertise or capital for investment, consolidation, defensive or pre-emptive purposes.
Geographic Strategy: The vendor's strategy to direct resources, skills and offerings to meet the specific needs of geographies outside the "home" or native geography, either directly or through partners, channels and subsidiaries as appropriate for that geography and market.
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