AI. Useful innovation or one step away from robot world domination?
We joke, AI might sound scary but reality is for working teams, there’s a lot to like about AI.
By embracing AI and working alongside it, it can make lots of tasks much easier and quicker - giving us more time and space to focus on the things that AI can’t do (yet!).
We are already incorporating AI into our daily lives at Cognism. This article aims to share our progress with AI adoption within our GTM teams, giving you an insight into what tools we’re using and how - so you can test them for yourselves.
Use the menu to navigate to the use cases that most interest you.
We’re so committed to exploring AI solutions that we have an OKR goal related to experimenting with and utilising AI tools in our daily workflows.
‘Operationalise the use of AI across the organisation in repeatable workflows’
Alice de Courcy, Cognism’s CMO said:
“I’m under no illusions that AI will be a part of our future, so I want to be in the first wave of B2B marketers implementing and utilising AI solutions in processes.”
“Which is why I’ve tied myself to an AI-related OKR. If part of my success as a CMO is measured against how well I encourage my teams to adopt AI tools into their daily processes then it makes it a focus and priority.”
“It also signposts to my team that I don’t view using AI as a lazy shortcut, but rather view it through a lens of finding ways to accelerate processes and experiment.”
So how are we actually using AI at Cognism so far? Keep reading to find out!
AI has endless use cases, and more emerge every day as new tools and technology are developed. Here are some of the use cases we use AI for at Cognism.
Content is one of the most obvious use cases for AI and a lot of the initial tools on the market were purpose built for easing the content process.
Our SEO team has been testing various free AI tools for identifying new keywords to target.
They fed objection-based Gong call transcripts into 5 free AI tools to find the one that best fit our requirements - here were the results:
Results were quite generic and not super useful in identifying new routes for keywords.
At this stage in Gemini’s AI development, it was unable to understand the task and therefore couldn’t complete.
Keyword suggestions were more long-tail and content-focused, which would be very useful for certain content projects. However, it was less so for our money keyword strategy.
Copy.ai suggested a lot of keywords that we already use. It would be helpful for those starting out with SEO work but didn’t help us to advance ours beyond our current setup.
Claude came out on top with much more interesting and helpful keyword suggestions. It was much more product-focused than the other AI tools, which made it far more valuable.
From this trial and error process, there was one obvious winner to keep testing - Claude.
Joe Barron, Senior SEO Content Manager at Cognism, says:
“I copy and paste the most relevant keywords into Ahrefs and do the normal keyword research for them.”
“From this I whittled 40 keywords to 10, then we pick out a handful to publish each quarter.”
Another useful tool worth mentioning around SEO is Frase. We have gone beyond just testing and have now cemented it into our SEO content process.
Why? Because it makes optimising content straightforward.
You put in your keyword - either writing your content directly into the platform or copying and pasting it from another document - and it will tell you where it ranks against the current available content online.
Making recommendations for where you need to focus your time when optimising. For example, it will tell you which supporting keywords to use and how many times. How many subheadings you should have. And what kind of length your article needs to be to compete with other content.
While you could also use Frase to create AI-generated content for you, we tend to prefer to keep the writing for our internal team as AI writing quality can become very generic.
Quality is our main priority, but it does make content optimisations a lot quicker, requiring much less manual research.
As we mentioned earlier, there are a lot of content use cases for AI. And SEO isn’t the only place where we are incorporating AI into workflows.
Our demand generation content team has also been experimenting with different AI tools. For things like:
These tools include:
Depending on the goal and content input, different tools come out on top. Here’s a summary:
As with any content marketing creation process, often the hardest bit is starting from a blank page.
It’s much easier when you have a starting point, from which you can edit and develop. That’s where AI chat tools such as ChatGPT come in handy.
You can give it prompts around what specific subject matter and points you want to cover - asking it to come up with a podcast outline with relevant questions for the guest.
While the questions ChatGPT spits out are never usually 100% the final ones we use - it offers a great starting point for the DG content managers to work from. Speeding up the process.
We have a full media machine that we like to maintain with regular content, including:
Repurposing long-form content into smaller, short-form pieces helps us ensure that we are distributing content efficiently across the media machine.
For example, we have a subject matter expert on our podcast, then we transcribe the podcast, allowing us to pull out sections we can share on social media or in newsletters.
If we had to manually transcribe this content, it would take hours.
But Descript allows us to do this in a matter of seconds to minutes. The transcripts aren’t always 100% accurate as sometimes words are misinterpreted but this is easily corrected with a proofread before it is used elsewhere.
Not only this, but Descript also has an AI search bar function - which means you can ask it to review the transcript it has created and pull out the main takeaways so you can share short sections of the text, as well as video.
Sticking with the repurposing content theme, Goldcast is the next tool on the list that we’re using.
You can edit live event recordings hosted via Goldcast, and ask it to pick and cut certain sections into snippets. These can later be shared on SME profiles or embedded into blog posts.
Either it will automatically choose sections it believes are the main takeaways, or you can direct it to take specific bits you want.
The platform also allows you to upload your own video templates - so you can input those AI-generated snippets into pre-designed, branded templates, which keeps all the videos looking uniform and on brand.
What’s the most annoying part of doing product research?
Most would probably agree it’s processing the vast amount of marketing data that can come out of this research. Because usually there’s so much of it that it’s overwhelming to make any sense of.
One of the solutions our team has discovered is APEX as a tool to make searching through existing research and messaging much easier and user friendly.
You can feed it documents and online content such as YouTube videos or online reports, and it will scan through it - allowing you to prompt it for specific takeaways.
Once research and messaging are loaded onto the tool, PMM can easily find answers across multiple sources.
It also has the capacity to scan images, a feature that many other summarising AI tools lack.
As with any AI adoption, you need to be careful how you implement it. But in B2B sales even more so.
As such a human facing role, relationship building and emotional intelligence are crucial qualities. Which so far, AI hasn’t fully grasped. Meaning over use could have a negative impact, such as obvious AI-generated emails or AI cold callers.
Until those tools are refined and harder to spot, here are some safer ways to implement AI for sales teams - ones we have tested out ourselves!
An important thing for our sales team to know is how we stack up against competitors in various ways. For example, what integrations are we compatible with versus our closest competitors.
These kinds of questions will come up regularly in sales conversations but might be hard to remember or stay up to date with.
Which is why we have recently introduced Crayon AI to Slack globally.
To enable sales to ask questions about competitors which will search our Crayon platform for answers in real time.
Kathy Thomson, Market Intelligence Manager for Cognism said:
“We have a fast growing sales team of hundreds of reps. With that much growth, competitive intelligence needs to be as easy as possible for reps to consume — we’re talking a few minutes tops. Crayon has been the ideal solution to meet that need.”
Reps are now consistently consuming intel and winning more competitive deals as a result.
We are heavy Gong users. And Gong, helpfully, has AI features within the platform which makes our sales team’s lives much easier!
Essentially, Gong’s AI pulls from all the recorded sales calls. For example, you want to know if there has ever been a conversation about budgets during a call with ABC account. You ask the AI, and it tells you based on all the data it has.
We use it to give us summaries of our sales calls, which we can then share with our prospects or use as a log of where we are at with deals.
Gong’s AI can also use these recordings to help you shape email outreach to these specific accounts using pain points and other important, useful information.
For those of you that didn’t know, we actually have an AI Search function within the Cognism product.
Don’t worry - this isn’t the part when we try to sell you it. But we do use it in-house ourselves so it’s worth mentioning.
Essentially, instead of manually searching for the right filter when looking for the right data, we can type or say what end search result we’re looking for. And the AI does the rest.
We have found that removing the manual filtering allows us to identify targets 74% faster!
Meaning we have improved sales team efficiency, increased data accuracy and increased market growth.
As a department, RevOps often implements new tech for other departments or solves unique problems for other teams, so there are fewer repeatable processes than can be automated by AI.
However, we have sound ways that AI can help.
Historically, our reporting has had to be very manual, mostly conducted through Salesforce. Building a number of dashboards for all different arms of the business, including AEs, SDRs, and Customer Success. But like anything, Salesforce has its limitations.
As Cognism has scaled, we’ve had a bigger need for streamlining in this department. Which led to us onboarding Tableau, where it migrated much of the key wider business reporting.
Before Tableau, a lot of time was spent creating reports and monthly RevOps decks for senior leadership on PowerPoint with screenshots from the Salesforce dashboards.
Implementing tools like Tableau meant they could reduce a lot of the time investment needed as they could automatically create decks.
AI tools are always developing, and we are always exploring new ways to use them in our teams. So, this list is unlikely to stay this way for long.
As we learn more about AI and how we can incorporate it into our daily workflows, we will add them to this blog post to keep our list fresh!