--- title: "Dig Insights Dig One competitive profile" source: internal-research created: "2026-04-24" status: active tags: [competitive, dig-insights, dig-one, upsiide, onecliq, storyteller, internal] --- # Competitive Profile: Dig Insights / Dig One Date checked: 2026-04-24 ## Scope This note profiles **Dig Insights** with a specific focus on **Dig One**, the product brand Dig launched to unify its technology stack. Important naming notes: - **Dig One** launched on **2026-02-17** as Dig's new umbrella platform brand. - **Upsiide** remains the core study creation / testing engine inside Dig One. - **OneCliq** remains the social-intelligence capability inside Dig One, now surfaced as **Social Reports**. - **Storyteller** appears to be the AI reporting layer inside the platform. - Current help-center taxonomy also references **Trends Tracker** and **Dig Labs**, but those capabilities were not deeply documented in this pass. Treat them as ecosystem signals, not fully profiled products. ## Executive summary - Dig is not just a SaaS vendor and not just a research consultancy. It is a **hybrid platform-plus-services competitor**. - Dig One matters because it is Dig's clearest attempt so far to close the gap between: - fast-turn insight work - strategic depth - defensible decision support - Their strongest USP is not a single AI feature. It is a connected operating model: - **discover** signals and language with OneCliq - **validate and forecast** with Upsiide - **turn results into stories and charts** with Storyteller - **back it with consultants, analytics, and data-quality controls** - Publicly, Dig is selling **connected decision-making**, not just faster survey execution. - Their strongest competitive advantages appear to be: - specialized innovation testing - behavior-oriented / choice-based methods - predictive analytics and market simulation - social / cultural context alongside survey testing - a stronger-than-average trust and data-quality posture - enterprise standardization support - The main uncertainties are: - how mature the full Dig One integration really is today - how broad the platform becomes beyond Upsiide + OneCliq + Storyteller - how much of the offering is productized software versus services-heavy enablement ## Company and platform snapshot Dig presents itself as a **tech-enabled insights company** focused on helping brands predict brand and innovation success. Current public signals: - founded in `2010` - `250+` strategists, consultants, developers, and data scientists - offices in Toronto, Chicago, and London - strong focus on brand and innovation decisions - explicit use of proprietary tools, AI, data science, and advanced analytics Their methodology story is unusually important because it shapes the product: - **Impulse drives decisions** - **Decisions occur in context** - **Attitudes alone do not predict decisions** - **Data needs to be actionable** That philosophy sits directly underneath Upsiide's product design and helps explain why Dig emphasizes behavioral testing and tradeoffs rather than plain opinion capture. ## What Dig One appears to be Dig One appears to be Dig's unified research environment for: 1. **discovery** 2. **testing** 3. **storytelling** Official help-center language says Dig One is an **end-to-end insights platform** designed to help teams make smarter, faster brand and innovation decisions. The strongest current read is that Dig One is Dig's answer to a fragmented insights stack: - one environment instead of separate tools - faster execution without losing methodological support - better connection between exploratory qual signals and structured quant validation - more stakeholder-ready outputs without exporting everything into separate reporting tools The launch messaging also leans into: - **connected decision-making** - **agentic intelligence** - **defensible analytics** - **control, transparency, and consistency** ## Detailed solution map ### 1. Discovery and cultural exploration The **OneCliq / Social Reports** layer is Dig's discovery engine. What it appears to do: - scan real-time online conversations across social platforms - surface themes, emotions, and drivers - identify cultural signals around categories, products, and competitors - reveal consumer language in the wild - help teams spot whitespace and early reactions - add context before a formal study is designed Dig frames OneCliq as meaningfully different from ordinary social listening: - not just counts, mentions, and fixed sentiment buckets - more about the "why" behind reactions - closer to automated qualitative interpretation at scale This matters commercially because it gives Dig a stronger **exploration / context** wedge than a standard concept-testing platform alone. ### 2. Structured testing and validation The **Upsiide Studies** layer is Dig's core testing engine. Publicly described use cases include testing: - products - services - positioning - claims - features - packaging - creative / communications - menu items Key product elements: - **Idea Screen** for large-scale early-stage idea screening - swipe-style respondent interaction - contextual tradeoff / commitment tasks - **Idea Split** for a smaller number of more developed ideas - survey logic, recall, targeting, templates, and dashboards - global audience access and multilingual studies The important competitive point is that Upsiide is not positioned as a generic survey builder. It is positioned as a **purpose-built innovation testing system**. ### 3. Forecasting and decision analytics This is one of Dig's stronger areas publicly. Vendor-claimed analytics stack includes: - **Idea Score** to predict in-market success - **Market Simulator** for: - share of choice - source of volume - incrementality - cannibalization - dashboards, filters, quadrant charts, and idea maps - norms and meta-analysis within standardized programs Dig's most defensible public wedge may be this combination of: - behavior-oriented input design - predictive scoring - business-facing market simulation That is a stronger value story than "we summarize responses faster." ### 4. Diagnostic feedback and optimization Dig also sells the platform as an optimization system, not just a winner-picker. Publicly described diagnostics include: - emoji-based emotional reaction capture - heatmaps that show what people like or dislike within an idea - open-end AI analysis - keyword / sentiment / theme extraction - quote-linked verbatim review - subgroup filtering - multilingual translation This gives them a more rounded workflow: - discover - test - understand why - improve the idea ### 5. Storytelling and stakeholder delivery The **Storyteller** layer is Dig's reporting surface. Current help-center docs say it can: - auto-generate stories for each audience - build custom stories with **Cobuilder** - tailor story objectives and included data - create custom charts - add commentary - apply statistical testing - share stories through guests or public links This is important because Dig is not just trying to speed up data collection. It is trying to compress the path from research result to stakeholder communication. Important maturity note: - current help content still labels Storyteller **Beta** ### 6. Cross-study memory and reusable knowledge Dig is not as explicit as some repository-first competitors about a universal research memory layer, but there are meaningful signals here: - Upsiide publicly describes a **searchable database** of all ideas ever tested - search works across markets and even across languages - Dig One as a brand is framed around connected thinking and reduced fragmentation - Research Live coverage paraphrases Dig's positioning as insights that can compound over time by drawing from every source Best current read: - Dig is moving toward a more connected research memory story - but its strongest public articulation is still around **connected workflow** and **tested idea history**, not a broad enterprise insight repository for every source under the sun ## What they do beyond the platform Dig's broader solution stack matters because many buyers will experience Dig as a partner, not only as software. Public solution areas include: - trends and foresight - jobs to be done - customer journey - demand space - co-creation - innovation sprints - innovation testing - winning at shelf - conjoint - innovation tracking - brand tracking - qualitative strategy - advanced analytics and data science The acquisitions reinforce this broader position: - **Ignite 360** added deeper qualitative and empathy-driven strategic work - **Ebco** added trends and innovation capabilities - **OneCliq** added social / cultural intelligence This means Dig One should be treated as the platform center of a broader insight-services ecosystem, not as a clean-room standalone tool. ## Their USP and how they sell it Dig's strongest USP appears to be: **A single, connected research operating model that combines cultural discovery, predictive innovation testing, AI reporting, and expert support without forcing a trade-off between strategic depth and speed.** More specifically, their commercial story rests on seven messages: 1. **You should not have to choose between speed and thoughtfulness.** This is the core launch message from the Dig One post. 2. **Insights work is too fragmented today.** Dig positions disconnected tools and weak partners as the real problem. 3. **Connected thinking beats isolated tools.** OneCliq + Upsiide + Storyteller is sold as a connected workflow. 4. **Behavior beats attitudes alone.** Their research philosophy is built into the product story. 5. **Fast is not enough; the output must be defensible.** Dig repeatedly uses language like rigorous, defensible, and leadership-ready. 6. **Standardization is a feature.** They sell Upsiide not only as a project tool but as an enterprise testing protocol. 7. **Software works better when paired with experts.** Dig does not hide the consulting layer. It uses it as part of the value proposition. ## Where they look strongest - **Innovation testing specialization** Upsiide looks more purpose-built for pre-launch innovation work than a generic research platform. - **Predictive business framing** Idea Score and Market Simulator give Dig a concrete bridge from respondent reactions to business outcomes. - **Qual + quant connection** OneCliq gives Dig a credible exploration layer that can feed Upsiide validation. - **Trust and data quality posture** Accessibility, in-platform controls, ESOMAR / vetted partners, and DQC integration create a stronger trust story than many AI-first entrants. - **Platform plus services packaging** Many buyers want guidance, not only software. Dig is well positioned for that. - **Enterprise standardization** Their standardized-testing program is a real differentiation point for larger organizations. - **Stakeholder-ready reporting** Storyteller plus sharing workflows help them speak to the "so what" bottleneck. ## Where they look weaker or less clear - **Integration maturity** Help-center language for OneCliq integration says this is the first step of the OneCliq journey within Dig One. That suggests the final product vision is still being built out. - **Brand architecture complexity** Public surfaces still mix: - Dig One - Upsiide - OneCliq - support.upsiide.com - app.upsiide.com - app.dig.one That can create some ambiguity about what the product boundary actually is. - **Storyteller maturity** Useful and promising, but still labeled Beta. - **Repository breadth** Dig is less explicit than repository-first competitors about being the place to query every research source across the enterprise. - **Public pricing clarity** Dig One pricing is not clearly surfaced. Older Upsiide pricing pages still appear publicly, which may not reflect the new platform packaging. - **Potential services dependence** Their expert-support layer is a strength, but it may also mean some value depends on onboarding, enablement, and consultancy involvement. ## Relevance for EmpathyIQ This is a meaningful competitor for any buyer seeking: - an end-to-end insight workflow - faster concept / package / claim / message decisions - stronger connection between exploration and validation - stakeholder-ready outputs from modern research tooling The overlap with EmpathyIQ is less about a narrow trust center comparison and more about: - connected insights work - reduced tool fragmentation - reusable decision support - decision-grade reporting Where Dig may currently feel ahead: - pre-launch innovation testing specialization - public market-simulation / incrementality story - integration of social / cultural exploration into the same commercial narrative - more visible services wrapper for enterprise buyers Where EmpathyIQ can still differentiate: - stronger governance-first positioning if that remains a strategic priority - broader research memory / operating-system framing if executed clearly - deeper emphasis on transparent reasoning and review logic - tighter narrative around insight knowledge reuse beyond innovation-testing workflows ## Practical takeaways 1. **Treat Dig as a hybrid competitor.** Comparing them only to software vendors will understate their offer. 2. **Their real wedge is connected workflow, not just faster surveys.** 3. **OneCliq makes them more than an innovation-testing tool.** It gives them a stronger cultural and language-discovery story. 4. **Upsiide is probably still the economic center of the platform.** It is the most mature and concretely differentiated capability in the public surface. 5. **Their trust story is stronger than average.** That will matter in enterprise evaluations. 6. **Watch Dig One over the next few quarters.** The integration and roadmap are moving, and the current public story suggests more capabilities are still being layered in. ## External sources checked on 2026-04-24 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -