B2B ad examples

You've spent years building your brand; make sure AI doesn't misrepresent it. Audit your citations and mentions across ChatGPT, Claude, and Gemini to ensure your value is coming through clearly.

Join Ian Whitestone (Co-founder and CEO, SELECT) and Olivier Soucy (Founder, Okube.ai) for a live workshop - "Databricks Autonomous Cost Optimization" - on Nov 12 @11am ET, and get tips on how to understand the seven levers that drive the most Databricks savings. Save your spot today!

What does it cost to run a frontier model as a customer support agent? Our G2 agent evaluations team measured it. We built an agent on 12 foundation models (22 configurations) from Anthropic, OpenAI and Alibaba. Each got the same one-page support policy and 38 live tools, and ran the same tasks as the vendor products on our CX AI agent leaderboard. Then we priced every token at list API rates. Five takeaways: 1. 𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝘀𝗰𝗼𝗿𝗲 𝗱𝗶𝗱 𝗻𝗼𝘁 𝗰𝗼𝗺𝗲 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 𝗺𝗼𝗱𝗲𝗹. Claude Sonnet 5.5 scored highest at 98.6% for 3.4¢ per conversation. Claude Opus 5.5 cost 2.4x as much at the same effort setting for a slightly lower score. 2. 𝗠𝗼𝗱𝗲𝗹 𝗰𝗼𝘀𝘁 𝗶𝘀 𝘀𝗺𝗮𝗹𝗹 𝗻𝗲𝘅𝘁 𝘁𝗼 𝘁𝗵𝗲 𝘁𝗶𝗰𝗸𝗲𝘁. 0.4¢ to 8.7¢ per conversation, vs. $0.99 per resolution for a leading CX agent and $5 to $10 for a human-handled ticket. 3. 𝗡𝗲𝘄𝗲𝗿 𝗺𝗼𝗱𝗲𝗹𝘀 𝘀𝗰𝗼𝗿𝗲 𝗵𝗶𝗴𝗵𝗲𝗿 𝗔𝗡𝗗 𝗰𝗼𝘀𝘁 𝗹𝗲𝘀𝘀. Across four Sonnet releases, the score rose about six points while cost per conversation fell 27% to 43%. 4. 𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝘂𝗽 𝗲𝗳𝗳𝗼𝗿𝘁 𝗺𝗼𝘃𝗲𝗱 𝗰𝗼𝘀𝘁 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗾𝘂𝗮𝗹𝗶𝘁𝘆. GPT-5 mini at high effort cost 4x as much for 0.7 points. 5. 𝗧𝗵𝗲 𝗯𝗶𝗹𝗹 𝗶𝘀 𝗺𝗼𝘀𝘁𝗹𝘆 𝗶𝗻𝗽𝘂𝘁 𝘁𝗼𝗸𝗲𝗻𝘀. The policy, tool definitions and conversation history are present every turn, so cached-input pricing sets the economics. The line I find most telling: the gap between the cheapest configuration and the best is about 3¢ per conversation, and 16 points of quality. For a support desk, choose quality first. Caveat: these are Tier 1 support tasks. Longer, harder tasks will raise costs for every model, and we expect the gaps to widen. Thank you to Cyril Delattre and our G2 agent evals team for building this. Full analysis and chart below.

Most supplier lists come from the same few sources: last year's RFQ, a fair, a colleague's tip. Speya looks across the whole market and checks every name it finds.

One customer ran the same category through Speya and through their usual search, side by side. What would your category show?

Bring more context to budget season. Expana’s 25,000+ analyst price projections draw on market fundamentals, pricing models and expert interpretation, looking up to three years out. Paired with 40,000+ commodity prices to inform procurement and finance planning.

Who is Expana? An independent market intelligence provider for the global agrifood sector. 40,000+ commodity prices across direct and indirect materials: ingredients, packaging, logistics, energy and labour. Add 25,000+ analyst price projections built on market fundamentals, pricing models and expert interpretation. Neutral data for procurement and finance teams.

OpenTelemetry s’impose progressivement comme un standard de l’observabilité. Mais entre Collector, pipelines, logs, métriques, traces et backends, le passage à la pratique peut sembler complexe. Ce guide a été conçu pour les équipes IT et exploitation qui veulent comprendre concrètement comment intégrer OpenTelemetry à leur environnement. Au programme : ✓ le parcours complet d’un log ✓ les principaux composants à connaître ✓ des exemples avec syslog, ELK et Graylog ✓ une méthode pour démarrer progressivement Un point de départ concret pour passer de la théorie à l’architecture.

Changer de solution de gestion des logs ne devrait pas vous obliger à reconstruire toute votre architecture. Avec OpenTelemetry, vous pouvez progressivement découpler la collecte de vos logs de leur backend de stockage ou d’analyse. Le guide Centreon vous explique comment : ✓ préserver l’existant ✓ standardiser progressivement vos flux ✓ préparer une migration sans rupture brutale Un guide concret pour les DSI, responsables IT et équipes d’exploitation qui veulent faire évoluer leur stack sans repartir de zéro.

Join AIUC + Collibra to learn how to supervise agents at scale and act fast when they cross the line.

Der Kunde kündigt. Die KI gratuliert zum Jubiläum. Die persönlichste Nachricht der Welt kann im falschen Moment alles verschlimmern. Stell dir einen Kunden beim Telekommunikationsanbieter vor. Sein Anschluss fällt wiederholt aus. Er hat die Störung mehrfach gemeldet. Jetzt wartet er auf eine Rückmeldung. Dann kommt eine Nachricht. Mit seinem Namen, seinem Tarif und einem Treueangebot zum Vertragsjubiläum. Nur zum kaputten Anschluss steht nichts darin. Das Marketing freut sich über die sauber ausgespielte Kampagne. Der Kunde denkt sich: Für Werbung reicht es offenbar. Für eine Antwort nicht. Er kündigt. Seine nächste passende Ansprache wäre ein Service-Update gewesen. Mit einem verlässlichen Bearbeitungsstand und einem konkreten nächsten Schritt. Genau daran musste ich bei der angekündigten Braze-Übernahme durch Salesforce denken. Der vereinbarte Unternehmenswert liegt bei rund 5,66 Milliarden US-Dollar. Der Abschluss wird im Salesforce-Geschäftsjahr 2028 erwartet. Aktionärszustimmung und regulatorische Freigaben stehen noch aus. Die gemeinsame Lösung ist eine Zukunftsperspektive. Das Vorhaben soll Kundendaten und personalisierte Ansprache enger verbinden. Weniger Übergaben und schnellere Reaktionen sind ein sinnvolles Ziel. Ob daraus bessere Kundenbeziehungen werden, entscheidet sich zwischen dem eingehenden Signal und der nächsten Aktion. Für die Szene oben braucht es drei Dinge. Der offene Servicefall muss rechtzeitig bei der Versandentscheidung ankommen. Mit eindeutiger Kundenzuordnung und aktuellem Status. Ein Datenabgleich in der Nacht hilft wenig, wenn die Werbung am Nachmittag rausgeht. Marketing und Service brauchen eine gemeinsame Vorrangregel. Bei einer wiederholten, ungelösten Störung pausiert das Treueangebot. Der Service übernimmt die Rückmeldung. Auch bei fehlenden oder veralteten Daten muss feststehen, was passieren darf. Die Entscheidung muss nachvollziehbar bleiben. Es muss erkennbar sein, welches Signal welche Nachricht ausgelöst oder verhindert hat. Ebenso muss feststehen, wer die Regel ändern darf und wann Werbung wieder freigegeben wird. Aus meiner Sicht gehört genau das zur Kundenbindung: verlässliche Daten, klare Zuständigkeiten und Regeln, die das Unternehmen selbst erklären und verändern kann. KI kann bei der Auswahl helfen. Den Vorrang des Service muss das Unternehmen festlegen. Manchmal ist die beste Marketingaktion eine zurückgehaltene Werbenachricht. Wenn du eine solche Kundenstrecke prüfen möchtest, schreib mir. Wir schauen gemeinsam auf Servicesignal, Vorrangregel und Versandentscheidung.

AI agents generate massive concurrent query loads. We ran 191,176 executions to see how 7 warehouses handle 100 simultaneous sessions.

The same workload costs $5.78/hr on one warehouse and $48.00/hr on another. See how all seven engines compare.

Multi-cloud shouldn't mean multiplying egress costs. Search federated across AWS, Azure, and GCP — without moving your data anywhere.

Telemetry keeps growing. Your pipeline shouldn't have to keep breaking. See how DataBahn gives security, observability, and AI teams one data layer to move, detect, and search telemetry without the rebuild.

Adding governance after OneStream go-live can mean rebuilding mappings you already paid to create. Starting earlier brings more work into an already busy implementation. Waiting can leave your team with mappings to revisit and another change process to introduce later. EPMware’s guide compares adding metadata governance before, during and after the project, including when OneStream’s own tools may be enough. Use the decision matrix to weigh the options against your systems, project timeline and audit needs.

How confident are you in the information used to manage your electricity network? Outdated or incomplete asset records can make it harder to identify maintenance needs, assess risks and plan network improvements. UNE for ArcGIS helps authorised employees keep network information up to date, supporting a more accurate view of your infrastructure. Give your teams the information they need to make informed decisions.

Network changes happen in the field. Your network data should keep pace. UNE for ArcGIS makes it easier for authorised employees to record network changes using applications designed for their roles. Explore how UNE can help your teams keep network information up to date.

𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗹𝗼𝗼𝗸 𝗯𝗲𝘆𝗼𝗻𝗱 𝗳𝘂𝘁𝘂𝗿𝗲𝘀 𝗺𝗮𝗿𝗸𝗲𝘁𝘀 𝘁𝗼 𝗯𝗲𝘁𝘁𝗲𝗿 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗱𝗮𝗶𝗿𝘆 𝗺𝗮𝗿𝗸𝗲𝘁 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀? “𝘛𝘩𝘦 𝘢𝘥𝘥𝘪𝘵𝘪𝘰𝘯 𝘰𝘧 𝘪𝘯𝘥𝘦𝘱𝘦𝘯𝘥𝘦𝘯𝘵 𝘥𝘢𝘪𝘳𝘺 𝘣𝘦𝘯𝘤𝘩𝘮𝘢𝘳𝘬𝘴 𝘩𝘢𝘴 𝘨𝘪𝘷𝘦𝘯 𝘶𝘴 𝘢 𝘮𝘶𝘤𝘩 𝘥𝘦𝘦𝘱𝘦𝘳 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘪𝘯𝘨 𝘰𝘧 𝘥𝘢𝘪𝘳𝘺 𝘮𝘢𝘳𝘬𝘦𝘵 𝘧𝘶𝘯𝘥𝘢𝘮𝘦𝘯𝘵𝘢𝘭𝘴. 𝘐𝘵 𝘩𝘦𝘭𝘱𝘴 𝘶𝘴 𝘭𝘰𝘰𝘬 𝘣𝘦𝘺𝘰𝘯𝘥 𝘧𝘶𝘵𝘶𝘳𝘦𝘴 𝘮𝘢𝘳𝘬𝘦𝘵𝘴 𝘢𝘭𝘰𝘯𝘦 𝘢𝘯𝘥 𝘱𝘳𝘰𝘷𝘪𝘥𝘦𝘴 𝘷𝘢𝘭𝘶𝘢𝘣𝘭𝘦 𝘪𝘯𝘱𝘶𝘵 𝘧𝘰𝘳 𝘰𝘶𝘳 𝘧𝘰𝘳𝘦𝘤𝘢𝘴𝘵𝘪𝘯𝘨 𝘮𝘰𝘥𝘦𝘭𝘴 𝘢𝘯𝘥 𝘮𝘪𝘭𝘬 𝘷𝘢𝘭𝘰𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴.” — Commodity Researcher and Systematic Trader, Cefetra Group Cefetra uses DCA Market Intelligence’s independent dairy benchmarks, pricing insights and market intelligence to build a broader view of physical dairy markets alongside futures markets. The team integrates DCA benchmark data into internal forecasting models, compares physical prices with futures markets and uses different dairy price streams to analyse milk valorization opportunities. Access to liquid dairy market data, historical benchmarks and WPC80 pricing also helps Cefetra follow developments across dairy commodities and ingredients in more detail. By combining independent benchmarks with its own models, Cefetra gains greater market transparency, improved forecasting capabilities and more informed commercial and risk management decisions. Read the full customer story on DCA Market Intelligence: https://lnkd.in/e-B2x6pY #DairyMarket #DCAMarketIntelligence #DairyBenchmarks #MarketIntelligence #CommodityTrading #DairyIndustry

I've lost count of the 11 p.m. close week calls from clients that started the same way: a consolidation load failed, and no one could say why. It's almost never the team. It's almost never the tool. It's usually one cost center that got created in the source system last Tuesday and never made it into the hierarchy the consolidation depends on. Someone hand-edits a flat file, reruns the load, and goes home. The number is wrong until it quietly isn't. After years around financial systems, I've come to believe this isn't an effort problem. It's a master data problem. The accounts, entities, and hierarchies underneath your close are the scaffolding for every number you report. When every system keeps its own copy and people maintain them by hand, they drift... and drift becomes failed loads, restated numbers, and audit findings. More people checking spreadsheets won't fix it. One governed source of truth that feeds every EPM and ERP system will. I wrote down how I think about it... link in the comments. If your close still runs on flat files and macros, I'm always up for comparing notes. #OfficeoftheCFO #FinancialClose #MasterDataManagement

If you're a quant, quant developer, market data and trading systems engineer, platform architect, data infrastructure leader, or SRE supporting trading environments at banks, hedge funds, brokerages, exchanges, and fintechs, you won't want to miss the free webinar from ClickHouse, in collaborating with Jefferies & Equiti Group.

You’re deep in legacy data, broken pipelines, and surprise schema changes. Now there’s Jev, new open source models, and Airflow Dags with loops??? If you’re feeling overwhelmed, you’re not alone. Join data engineers Tamara and Volker on November 18 for an honest conversation about what’s worth your attention and what you can safely ignore. Here’s what to expect: → Two data engineers trying to decipher the current trends → Where your role is headed (it’s not all bad!) → Resources and code to take home

𝗠𝗶𝗹𝗸 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗴𝗿𝗼𝘄𝘁𝗵 𝘄𝗲𝗮𝗸𝗲𝗻𝗲𝗱 𝗮𝗰𝗿𝗼𝘀𝘀 𝗘𝘂𝗿𝗼𝗽𝗲𝗮𝗻 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 𝗶𝗻 𝗦𝗲𝗽𝘁𝗲𝗺𝗯𝗲𝗿 Germany recorded the biggest change, with collections down 4.3% year-on-year after rising 3.1% in August. France was almost unchanged, while Poland increased. Year-to-date production is still above 2025 levels in all three countries, mainly because of stronger growth earlier in the year. Milk prices remain under pressure, despite recovering from August. Feed costs have eased in several markets, but lower milk prices continue to put pressure on margins. Read the full DCA Market Intelligence analysis by Santiago Morales Hilarión: https://lnkd.in/ePpn_Jjb #DairyMarkets #MilkProduction #MilkPrices #EuropeanDairy #FarmgateMilk #DCAMarketIntelligence

Vos commerciaux perdent encore du temps sur les mauvais contacts ? Aidez-les à atteindre les décideurs qui comptent vraiment.