What is our primary use case?
I have been using Odigo for two years now. During my first year, I received training about all the tools available in my organization, and after that I was onboard on Odigo.
For me and my team in my organization, we use Odigo for customer experiences. We use it as our customer managing tool. Instead of managing customer inquiries individually, we use Odigo to centralize multiple communication touchpoints into a single platform. Odigo has an agent which can seamlessly handle inbound and outbound communications across multiple channels including voice, email, web chat, and others. This helps us interact with customers and reach out to them when we have any product to sell or negotiate with them.
Since Odigo has AI-powered self-services and intent qualification, there was a customer who was frustrated and scanned a QR code on their bill which initiated a WhatsApp text. This was routed through Odigo. Odigo has natural language processing called NLP, which digitally analyzed the message "Why is my account blocked?" In this scenario, the customer was frustrated and asked why their account was blocked, stating they had already paid their base bill. The communication was directly routed to an agent in Odigo, which we call a bot. The bot securely authenticated the customer's phone number, fetched account data details from the backend during the billing engine, and identified the exact culprit, for example, forty-five dollars in international roaming data charges. The bot itself explained the charge. However, the customer texted, "I had an international pack active. This is an error. I need to speak to someone." Odigo then routed the interaction to a human agent. This is an example which I recently observed working with Odigo and the customer. First-line contacts are transferred to the bot or agent, and in case the agent is unable to assist fully, these interactions are offered to human agents, such as my teammates.
Regarding high-grade audio architectures, Odigo provides high voice quality which operates its own international telecommunication infrastructure. This boosts the mean opinion scores for voice quality. There is no lag while talking with customers. For a contact center, audio has minimal latency and packet loss which directly impacts how smoothly an agent can communicate with the client. This applies not only to agents but also to me, my organization, and my team.
What is most valuable?
Regarding the best features, Odigo has robust Salesforce and all CRM native connectors. Odigo is not solely a tool. We can interact with, configure, or integrate with multiple CRM tools. For our case, we have Salesforce and ServiceNow. For interactions, we use Odigo itself, which has robust CRM processes. Instead of relying on complex customer development or heavy middleware, Odigo offers highly stable API-first native connectors for enterprises and CRMs, which has a unified console and instantaneous pop-ups. It fetches real customer history and account data and instantly gives immediate context to us. Additionally, it has conventional AI and natural understanding. Voice bots, which are agents, traditionally required voice commands such as press one for this or press two for that option, are now replaced by natural language processing. Our customers are no longer required to press digits. Our agents directly interact with customers in the same manner as a human would. For instance, I am speaking with Samantha right now. Similarly, Odigo talks with our different customers. In case a customer still says, "I want to talk with a human executive, someone in the team," Odigo acknowledges that and these communications and interactions are offered to a real human being. Odigo offers pretty well and useful features currently.
Regarding the unified console, when rolling out a unified console such as Odigo, especially in an environment tied with multiple enterprises such as Salesforce or ServiceNow, my team members and agents generally experience a massive shift in their daily workflow. Feedback from frontline support scores and administrative functions shows significant relief along with a few technical adjustments such as screen pop-ups that boost confidence. Agents working with Odigo feel much more confident taking inbound calls and answering them when the console instantly shows a customer profile pop-up. It already knows the customer's name, their history, and their open cases before saying hello to them. This narrates everything so that customers feel acknowledged and saves time for the customers. Additionally, it eliminates repetitive interrogation phases of the call. It keeps the interaction with the agent human-like, which has adjustment phases. Switching between different contexts, the stability, and the interface design is very natural and very positive. The agent is cautious while talking with customers and gives sufficient time for the customer to speak. It does not interrupt in between. This has given us much impact.
Regarding my specific organization, deploying a platform such as Odigo helps organizations across multiple departments, not only in sales, commercial, or marketing, but also in IT operations, platform teams, commercial operations, and pre-sales. It gives us operational efficiency and cost control. Odigo heavily reduces administration and handling and automatically handles the friction that slows the customer support ecosystem. For example, reducing after-call work because the platform uses integrated AI to automatically transcribe the call and draft interaction notes directly into CRM cases. Agents save a lot of time for us. Even if it saves time for us, it also saves costs for our company. It likely reduces the full-time employee count. We can manage people in different shifts and manage our customers with fewer people. Additionally, it has fewer lost transfers because skill-based routing connects the customer to the correct technical team. Multiple times the time is not wasted routing the case from one team to another. The agent specifies from which team the case needs to be addressed. According to that, this is saving us a lot of costs, time, infrastructure, tools, and everything else. Additionally, it is making the customer experience better.
What needs improvement?
There are several areas for improvement that Odigo could enhance. As a starting point, Odigo could enhance their AI to be even more empathetic and capable of understanding complex emotional nuances in real time. That would be the best solution. This would enable bots to de-escalate frustrated customers more efficiently. Another area is user interface customization, which could allow agents to personalize their dashboards. This is not just for agents but for all people working with us, which could more effectively reduce cognitive overload and make the unified console feel more agile for different workflows. One more example could be integrating deeper with predictive analytics which could help organizations foresee potential service disruptions before they impact customers, which allows more productive communication for us. The AI cannot be directly improved in all cases, but it needs probably many iterations to improve day by day. However, we have seen a lot of growth and enhancement with the AI agent as well. The user interface can be improved more effectively so that we are able to prepare a dashboard for ourselves, which can monitor the ongoing calls both inbound and outbound.
For how long have I used the solution?
I have been working in my current field for more than three and a half years. I joined at the start of 2023 in January 2023. Since then, this is my first company. I have been working for three and a half years.
What do I think about the stability of the solution?
Odigo is widely considered as one of the stable providers because of its unique foundation as both a software provider and international telecommunication carrier. One of the key indicators is the audio reliability which has a high mean opinion score for voice quality and minimal latency even during peak call volumes. Its cloud-native architecture is designed to scale elastically, allowing it to handle massive traffic surges without experiencing system crashes or degraded service. All these factors contribute to a very dependable platform for enterprises.
What do I think about the scalability of the solution?
Regarding scalability, one of Odigo's strongest points is its cloud-native architecture designed for elasticity itself. For us, this means that the platform can effortlessly handle massive spikes in concurrent audio and digital interactions, managing millions of calls for us globally, locally, and regionally without any drop in performance or voice quality. To date, we have not faced any service disruptions with Odigo, even when there is major traffic and major surges in our operations. In terms of scalability, Odigo's performance is managed effectively.
How are customer service and support?
Odigo's customer support is generally seen as quite attentive and technical, especially for enterprises such as us because they operate their own telecom network as well as the software. Their support teams are often well-equipped to handle complex configurations and integration issues. Typically, they offer different levels of support depending on the service agreement, including dedicated account managers and twenty-four-seven assistance for critical incidents. We have seen very well-managed services with customer care from Odigo.
It is challenging to rate the customer service because its experience can vary depending on the service level. However, generally, it is considered strong, especially for enterprises such as us, which offers dedicated account management and technical support for enterprises. I would definitely rate it around eight because it has direct access to carrier-grade support.
Which solution did I use previously and why did I switch?
We have been using Odigo from the start. We do not have any alternate option currently.
How was the initial setup?
For organizations looking into using Odigo, the first piece of advice is to focus heavily on how deeply it integrates with your existing CRM, which might be anything such as Zoho, Salesforce, ServiceNow, or anything else. That is where the biggest efficiency gains are seen. Second advice might be to ensure you leverage Odigo's carrier-grade voice to ensure crystal clear audio which is critical for customer satisfaction during peak times. The lastly, plan for the adaptation caused by training your agents on the unified console so that they can fully utilize its features without feeling overwhelmed. I would definitely give this kind of suggestion and advice to them and I would encourage them to use Odigo.
What was our ROI?
Absolutely. Our average handling time drops by fifteen to twenty-five percent since the native Salesforce CRM connector; we managed to make the SLA positive from ninety to ninety-five percent. Previously, our team consisted of fifty headcount. Now we are managing with thirty-five people only. This has saved us after-call work. Instead of the human agent spending two to three minutes typing, wrapping notes and transcribing and summarizing everything after the call ends, it saves a lot of time. It also reduces minor and major escalations for us since first contact resolution has increased by ten to fifteen percent. Utilizing advanced context and skill-based routing, calls are pre-qualified via NLP natural language processing and then routed to the exact technical specialist equipped to handle the specific issue. This vastly reduces the need for internal end-to-end transfers. We have different levels of teams in our organization. However, specific interactions and customer issues are routed to the correct team. This saves the SLA, costs, timing, infrastructure, and everything for us. Since Odigo is based on a cloud-based platform, we are no longer required to have physical infrastructure for this. We can work remotely and we can work in the office as well. We work in a hybrid model.
What's my experience with pricing, setup cost, and licensing?
We have seen twenty to thirty percent inbound call deflation by utilizing Odigo's AI-powered conventional voices and digital bots to handle repetitive tasks such as tier-one tasks, including simple account verification, password reset, or payment status check. Up to nearly a third of inbound volume is completely resolved via self-service. Optimizing staffing allocations means that deflecting those basic calls means your highly trained human resources are no longer bogged down by administrative loops. They are freed up to focus entirely on complex high-value problem-solving which stabilizes your overhead costs. In terms of time, there is a fifty to twenty percent reduction in average handling time thanks to the native CRM connector such as Salesforce; the system triggers an instantaneous screen pop-up loading the user's exact history and digital chat right on connection. This improves the standard by sixty to ninety seconds typically wasted asking clients to manually verify their name and repeat their problem. We have seen up to a forty percent reduction in after-call work. Instead of advisors spending two to three minutes typically detailing notes after hanging up, Odigo's integrated AI automatically transcripts the audio, interacts with the core problem and resolution, and logs a structured summary directed into the CRM object field. This allows agents to stay back into the live queue instantly. We have seen a twenty to thirty percent lower IT infrastructure cost. Moving to Odigo allows our organization to eliminate multiple fragmented licensing bills. We no longer need to pay separate vendors for softphones, voice recording servers, standalone routing software, and third-party telecom trunk lines. This has saved us considerable cost for us. It has consolidated carrier cloud and eliminated separate billing for software and recorders, and other things.
Which other solutions did I evaluate?
My organization has been using Odigo since I joined this company. However, regarding the decision-making, I am not certain because my organization has been using Odigo for a longer period.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?