Customer-Insights-Analysten
Vertrieb und MarketingKI-Exposition
- Datenquelle: BLSVeröffentlicht: 2026-08
Sehr hoch· relativ
NiedrigVier relative BänderSehr hochWert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)
831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band
- Datenquelle: AnthropicVeröffentlicht: 2026-03
0.648
0.000Spannweite der hier geführten Werte0.745Skala, Bezugsmenge und Quelle
Index der beobachteten Exposition, 0–1 wie veröffentlicht
Auf O*NET-Aufgaben abgebildet
- Datenquelle: ILOVeröffentlicht: 2025
0.55
0.09Spannweite der hier geführten Werte0.70Wert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht
ISCO-08-Berufsgattung — alle Berufe mit demselben Code erhalten diesen Wert
Von dieser Website berechnet, nicht von der IAO veröffentlicht: Von den 1.012 Berufen, die diese Website mit dem IAO-Datensatz verknüpft, erreichen oder übertreffen 12% diesen Wert.
Welche Art von Wert diese Quelle veröffentlicht
Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.
Task-level exposure
33 ausgeblendete Aufgaben anzeigen| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Develop transactional Web applications, using Web programming software and knowledge of programming languages, such as hypertext markup language (HTML) and extensible markup language (XML).13-1161 | 0.170031.5 | 0.06008.3 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.13-1161 | 0.090016.7 | 0.04005.6 |
Implement online customer service processes to ensure positive and consistent user experiences.13-1161 | 0.080014.8 | 0.390054.2 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.13-1161 | 0.05009.3 | 0.02002.8 |
Conduct market research analysis to identify search query trends, real-time search and news media activity, popular social media topics, electronic commerce trends, market opportunities, or competitor performance.13-1161 | 0.02003.7 | 0.06008.3 |
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.13-1161 | 0.02003.7 | 0.04005.6 |
Forecast and track marketing and sales trends, analyzing collected data.13-1161 | 0.02003.7 | 0.01001.4 |
Prepare electronic commerce designs or prototypes, such as storyboards, mock-ups, or other content, using graphics design software.13-1161 | 0.02003.7 | 0.01001.4 |
Identify and develop commercial or technical specifications, such as usability, pricing, checkout, or data security, to promote transactional internet-enabled commerce functionality.13-1161 | 0.02003.7 | 0.00000.0 |
Optimize Web site exposure by analyzing search engine patterns to direct online placement of keywords or other content.13-1161 | 0.01001.9 | 0.02002.8 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.O*NET Task ID 5433 | 0.5 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.O*NET Task ID 5434 | 0.5 |
Measure and assess customer and employee satisfaction.O*NET Task ID 5435 | 0.5 |
Forecast and track marketing and sales trends, analyzing collected data.O*NET Task ID 5436 | 0.5 |
Seek and provide information to help companies determine their position in the marketplace.O*NET Task ID 5437 | 0.5 |
Measure the effectiveness of marketing, advertising, and communications programs and strategies.O*NET Task ID 5438 | 0.5 |
Conduct research on consumer opinions and marketing strategies, collaborating with marketing professionals, statisticians, pollsters, and other professionals.O*NET Task ID 5439 | 0.5 |
Attend staff conferences to provide management with information and proposals concerning the promotion, distribution, design, and pricing of company products or services.O*NET Task ID 5440 | 0.5 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.O*NET Task ID 5441 | 0.5 |
Monitor industry statistics and follow trends in trade literature.O*NET Task ID 5442 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
Berufsinformationen
Aktuelle Veränderungen mit Bezug zu diesem Beruf
März 2026: Gupta & Kumar (arXiv, Mar 2026) give Market Research Analysts an Agentic Task Exposure (ATE) score of 0.43 by 2027 in the San Francisco Bay Area (Tier 1), rising to 0.47 by 2030. That crosses the moderate-risk threshold (0.35) in 2027, when Tier 2 metros (Seattle, Austin, Boston) have no crossings yet.
[Quelle: arXiv 2604.00186 (Gupta & Kumar, 2026)]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.