In the time it will take you to listen to this podcast episode, parts of it might already be out of date. AI is evolving at a breathtaking pace, yet most companies still struggle with adding it to their workflows in ways which will add business value. And this is the uncomfortable truth that few have addressed head-on: if AI can improve your employees’ efficiency and productivity, but you apply it to the wrong tasks, it could be doing more harm than good.

In our new podcast episode, Mammoth Growth CTO Drew Beaupre interviews Ethan Aaron, CEO and Founder of Portable. Ethan and his team at Portable are well on their way to building a platform that can manage integrations with 10,000 other systems. What’s surprising here is not the pace of their growth, but Ethan’s unconventional take on AI. Upon hearing of Portable’s success, most people’s knee-jerk reaction is to suggest AI as a method for automatically building these API calls even more quickly. But Ethan points out something very few other people are talking about: the real test of AI is whether it can add value to the business based upon each of these new integrations. Connecting one app to another just to move data only has limited value, until we can find ways to surface and activate data that can help companies hit their goals.

Ethan’s perspective on AI as it relates to Portable highlights a much larger issue facing every company right now. AI is not the product itself, but simply a tool that can be used to enhance other products by automating tasks and aiding decision-making. If we don’t clarify what types of behavior we need to change to hit our goals, AI won’t help us make better decisions. If we don’t trust the data we’re handing over to AI, or if we’re feeding it inaccurate data, then again, AI won’t help us make better decisions. On its own, AI is not a guarantor of faster, more accurate insights. First, we must understand our business and our data to the best of our ability. Only then can AI deliver on its insane potential.

Right now, AI is an answer in search of a question. But ironically, AI has revealed a universal truth that savvy marketers have known for decades. AI will allow people to build similar products faster than ever before. And that means that if everyone competes on features and price, commoditization is inevitable as we race to the bottom. The only way to avoid being squashed by this trend in the years to come is to focus on your brand. AI can help you build your website faster, produce content more quickly, and shorten development time for your product. But it can’t tell you what your brand should be, or what it could be. As Drew and Aaron point out, that’s up to you. And that’s something that will never be out of date.

Thanks for listening!

Visit us at: MammothGrowth.com
Follow us on LinkedIn

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Since 2015, over 850 companies have trusted Mammoth Growth to surpass their marketing, product, and business intelligence goals. We offer consulting, integration, and strategic planning services in the following areas:

- Data Engineering / Governance
- BI Reporting & Dashboarding
- Customer Data Platform (CDP)
- Product & Behavioral Analytics
- Lifecycle / Email Marketing
- Modern Data Pipelines
- Multi-Touch Attribution
- Machine Learning
- A/B Testing

Mammoth Growth has deep expertise in a wide range of tools, including Amplitude, Braze, Heap, Mixpanel, Optimizely, Rudderstack, and Segment.

We’re your Growth Team as a Service.

It’s the foundation of every technological initiative. But what happens if you build on a shaky foundation? Data governance is frequently missing from conversations about the value of product analytics, and Avo is out to change that. In this episode of the Mammoth Growth Podcast, Avo CEO and Co-Founder Stefania Olafsdottir chats with our EMEA President Stuart Scott about the challenges companies face with poor data governance, and how they can resolve these issues and spend more time building great products.

Product analytics is a discipline just like sales or marketing, and just like these, it will reward a high level of planning. While it’s one thing to understand the impact of a company’s product analytics on their overall decision making (analytics for your analytics), data governance addresses the very core of product analytics:

• How can we possibly make good decisions with bad data?
• How do we restore trust in our data?
• If we have a gatekeeper to confirm data quality before we ship, how do we deal with that bottleneck?
• How do we ship accurate product analytics based on good data, faster?

Stefania has seen this sequence play out over and over again, from really bad data to good data to self-serve data governance for product analytics. 

One of Stefania’s breakthroughs was starting small, by finding the one person on a team who was passionate about data quality. Starting there, it’s much easier to demonstrate success with data governance by focusing on tactical wins - for example, improving adoption of one feature at a time, or increasing the conversion rate for a single cohort of users. How to approach data governance projects is just as important as the technology you implement along the way. Stefania’s insights into successful data governance led her and her team to create Avo, which fixes data quality for product analytics so every company can build on a solid foundation.

Thanks for listening!

Visit us at: MammothGrowth.com
Follow us on LinkedIn

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Since 2015, over 850 companies have trusted Mammoth Growth to surpass their marketing, product, and business intelligence goals. We offer consulting, integration, and strategic planning services in the following areas:

- Data Engineering / Governance
- BI Reporting & Dashboarding
- Customer Data Platform (CDP)
- Product & Behavioral Analytics
- Lifecycle / Email Marketing
- Modern Data Pipelines
- Multi-Touch Attribution
- Machine Learning
- A/B Testing

Mammoth Growth has deep expertise in a wide range of tools, including Amplitude, Braze, Heap, Mixpanel, Optimizely, Rudderstack, and Segment.

We’re your Growth Team as a Service.

Analytics teams are positioned to guide everyone in a company to make better decisions. But how well are companies measuring the performance of their analytics teams? What types of questions are they dealing with, and how do their actions impact the company’s growth trajectory?

We dive into these topics and much more in the latest episode of our podcast. Our CTO Drew Beaupre chats with Osman Ghandour, Co-Founder of Soal Data. Osman explains that ad hoc analytics refers to unplanned, reactive work that data and analytics teams often have to handle. While this type of work can easily be seen as a distraction, it can also be an opportunity for these teams to ease decision-making throughout a company. As Osman points out, there’s a fine line between resolving a one-time ask vs recognizing the types of questions that come up over and over again. Soal Data’s mission is to shine a light on all types of analytics questions, to show which ad hoc requests should be given more close attention. Drew clarifies their value this way: if analytics and data teams receive repeat ad hoc requests of a similar nature, there’s a much higher likelihood that those requests point to valuable areas for the business to focus on. Soal Data helps companies identify these patterns automatically. Think of their solution as analytics for your analytics. 

Data and analytics teams can be structured in three distinct ways to address ad hoc requests:

No special structure. A company’s existing analytics and data teams must drop whatever they’re doing whenever an ad hoc request comes in. In this scenario, the same people must manage proactive and reactive work at the same time. While this scenario is the most common, it’s also the most likely to increase context switching, burnout, and employee turnover.

1) A hybrid approach rotates the responsibility for addressing ad hoc requests among different members of the analytics and data teams on a weekly basis. This scenario reduces context switching and its associated burnout, and it has the added benefit of giving everyone on the team a broader perspective of what the team is working on.

2) The fully dedicated ad hoc team. Osman often sees this setup in certain industries that receive a non-stop flow of questions, especially in insurance, finance, or anything related to compliance.

Osman highlights the importance of measuring the value of ad hoc work, since today’s ad hoc requests might very easily become part of a company’s product roadmap tomorrow. Soal Data allows companies to identify that tipping point quickly and efficiently.

Thanks for listening!

Visit us at: MammothGrowth.com
Follow us on LinkedIn

-------
Since 2015, over 850 companies have trusted Mammoth Growth to surpass their marketing, product, and business intelligence goals. We offer consulting, integration, and strategic planning services in the following areas:

- Data Engineering / Governance
- BI Reporting & Dashboarding
- Customer Data Platform (CDP)
- Product & Behavioral Analytics
- Lifecycle / Email Marketing
- Modern Data Pipelines
- Multi-Touch Attribution
- Machine Learning
- A/B Testing

Mammoth Growth has deep expertise in a wide range of tools, including Amplitude, Braze, Heap, Mixpanel, Optimizely, Rudderstack, and Segment.

We’re your Growth Team as a Service.