Contributed by: Margaret Dron
After months of researching and testing AI-powered tools that could benefit Analyst Relations leaders - 83 to be exact - it's clear that AI can be a powerful extension for many AR teams.
And although leaving AI-powered tools out of their toolbox could put AR teams at a disadvantage, I've heard many share that it's challenging to know where to start, and how to create impactful workflows.
You're not alone. Even as someone who's been immersed in AI for almost 5 years, it took a lot of mapping, testing, and (admittedly) errors to get a solid grip on tools and optimal workflows for Analyst Relations.
My hope is to make it easier for you. Due to the depth of this topic, findings will be shared in 2 parts:
Which AI-powered tools could have a meaningful impact on your AR programs.
Combining them into effective tech stacks and optimized AR workflows [coming soon].
By the way, if you have questions, comments, or need guidance with implementing AI into your Analyst Relations program, please connect, I’d love to hear from you.
Impactful Ways Analyst Relations can benefit from AI
Most leaders I've spoken with understand the positive impact AI can have on competitive intelligence and project management efforts; however, there's a feeling of uncertainty regarding how else AI can help them succeed. For this reason, I’ll focus on the following three areas today:
Analyst and Network Analysis: see what Analysts are saying regarding your company and competitors on social media, while also identifying trends, influential connections, and sentiments to strengthen your AR strategy. Who might be influencing your influencers?
Sentiment Analysis: get ahead of the narrative by using natural language processing and machine learning to gauge sentiment during Analyst interactions, Briefings, and preliminary customer reference interviews.
Personalization: maximize engagement and impact with AI-supported organization, distribution, and hyper-personalization for Industry Analysts and internal Stakeholders.
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What is AI?
According to Chat-GPT: “Artificial intelligence (AI), refers to computer systems that can perform tasks that typically require human intelligence for things like learning, problem-solving, decision-making, and natural language processing.”
For Analyst Relations leaders tasked with finding ways to achieve more with less, quicker, and more economically, AI can act as a powerful extension to your team.
In addition to automating repetitive tasks and workflows to free you for higher-value activities, you can effortlessly identify patterns, trends, and correlations that can help inform your strategy and decision-making.
For example, is one Industry Analyst costing you twice as much as a second, yet mentioning your competitor 3x more often than your company, and resulting in only a small fraction of the revenue impact of the second? AI can help you track, analyze, and report on this for future budget allocation and strategy improvements.
But first, a word of caution. Always keep in mind that the output can only be as good as the input, so it’s important to dedicate time, in the beginning, to thoroughly examine your data sources for accuracy, along with their relevant policies, collection methods, and security measures.
Where to Start
If getting budget approval for new technology is an obstacle, start by determining where AI tools can help you reduce costs. Cost-saving pilots are sometimes easier to get in the door as a first point of entry. An easy place to start is to identify time-consuming or repetitive tasks, then track the time spent on each one monthly or annually. Multiply the potential time saved by the cost of that time. If possible, also incorporate the value that could be added by freeing the teams' for other high-value matters.
Once you've identified the areas of opportunity, explore vendors who offer AI solutions to streamline those tasks. For instance, you might find that sifting through mountains of data to find key insights is eating up too much of your time. AI can help there! Or perhaps you're spending hours each week manually tracking analyst reports and internal use of them. AI can automate that process and free up your time for more strategic activities. There are countless ways to apply AI to minimize the time and resources your team spends on repetitive tasks. And if you're able to reduce costs significantly enough, your pilot project may pay for itself while building a clear case for further investment in next year’s budget.
Perform an internal Audit of tools that your organization is already using within other teams. Many groups like Sales, marketing, and communications are already utilizing tools that can be re-purposed to benefit Analyst Relations programs. It’s amazing what can be effectively repurposed. Remember, just because these tools are not marketed to us, does not mean they can’t also perform meaningful and impactful work for us in Analyst Relations. 😊
Look for tools that mostly work out of the box. The fewer additional company resources needed, the greater your chance of approval when you start down this path. Although many AI tools need access to quality data at scale to produce results, many offer easy integration tools that you can activate yourself. Therefore, only needs IT signoff, rather than integration and maintenance support.
Platforms to consider:
There are many out there, with more being created by the day it seems. Of the 83 AI tools I’ve tested, these are the ones I’ve personally shortlisted for my toolkit.
It’s important to note that in addition to capabilities, I also prioritized tools that either only require minimal IT assistance, can be used as a standalone system indifferent of which other technology your company uses, and/or solutions that are likely already used within an organization and can be easily repurposed for AR needs.
1. Analyst Tracking
Keeping track of what analysts are saying about your company and competitors online is an important, but time-consuming practice that AI can easily assist you with.
All of the tools below can track specific analysts on a number of social media platforms for you, company websites, and other information sources. Research their interests, preferences, and brand mentions. Their value ramps up significantly once you set up Analyst streams and vertical groups, as well as trend tracking, influencer identification, sentiment analysis, and data visualization.
Tip: Maximize your impact by observing who’s influencing your influencers by considering interactions they’re having with others on social media.
Tools:
You may find that your organization is already using something similar to these within its Marketing or Communication teams. Gong is a little different as it’s typically used by sales or sales enablement teams.
Identify trends, track sentiment, engage and develop more effective analyst relations strategies. However, as always, be mindful of ethical considerations when using these tools, and always respect analysts' privacy.
2. Sentiment Analysis
Analyze sentiment during Analyst interactions like Briefings and Inquiries, and improve spokesperson training with tools like:
You may find that your organization is already using Salesforce and Gong within its sales, or sales enablement teams. Although Gong can be used as a standalone solution, it’s important to note that Salesforce Einstein is only available as an add-on for Salesforce customers.
Qualtrics dscvr (Discover) is most often a tool that contact centers, or service, and support teams would turn to. So, you may want to check with those teams in your organization to see if it’s possible to add on a single license for Analyst Relations. AR is not their usual target market; however, we could benefit greatly from its feature set.
Important note: accuracy increases with volume for system training, so there are a number of considerations to take into account prior to investing in this particular AI.
3. Personalization
Maximize engagement and impact by analyzing stakeholder needs and preferences to deliver hyper-personalized experiences. For now, we’ll focus on the organization and personalization of information.
Internally, this can streamline AR information access and utilization. Externally, this can provide Industry Analysts with highly personalized experiences throughout your company's Analyst portal.
Note: although I did test multiple AI-based predictive analysis platforms, I didn’t find one that checked the boxes and produced accurate and optimal insights for an AR use case. For this reason, this area was considered; but, left out.
1. Organization
According to the State of Analyst Relations report, only 16% of respondents use an AR Management platform for tracking, analysis, and reporting. It was also surprising to learn how many AR leaders are relying on MS Excel or Google Sheets to organize this important information. Although spreadsheets are the easiest to set up, they are quite limiting and time-consuming to gain insights from. Especially when compared to alternative platforms.
There are a lot of out-of-the-box CRM platforms you can use; however, not many have yet integrated AI-powered features that “just work”. Although I’d imagine many will in the coming months. For now, the one I decided to personally use is Hubspot.
I’ve found it easy to create custom fields and categories that allow me to organize Analysts by industry, archetype, and firm. Its email and integration tools also make it effortless to track interaction dates, notes, and files. The workflow for different engagements is also a nice bonus.
The challenge with using a CRM system already utilized within your organization, like Salesforce for example, is that you will likely be unable to customize the fields and reports in such a way that it benefits Analyst Relations. This is one tool that usually needs to be a stand-alone product specifically for Analyst Relations.
2. Personalization
Imagine creating a responsive chatbot that delivers tailored experiences to Analysts while also quickly connecting marketing, sales, and communications teams with the analyst-generated reports, recordings, and competitive Intel they need. All conveniently and securely accessed from your analyst portal. A portal that welcomes each visitor with messaging, and materials that are tailored to them.
Shortlisted AI-Powered Chatbot solutions that utilize natural language processing:
Admittedly, these can be a little challenging to implement without some technical assistance. As the potential ROI is significant, I’ll still take a moment to run through these quickly for you.
OpenAI: Specifically, the new Chat-GPT Business subscription tier which is being released soon. It’s designed for enterprise businesses as a private version of their Chat GPT Pro, and prevents your company's data from being used to train Chat-GPT - protecting your company’s privacy.
Dialogflow: a Google Cloud-based tool for building conversational interfaces such as chatbots and voice assistants. The tool offers pre-built templates and integration options for a variety of popular messaging platforms.
IBM Watson Assistant: uses NLP and machine learning to understand queries and provide relevant responses. IBM Watson Assistant also offers pre-built templates and integrations.
Personalized content and messaging:
Marketo: content intelligence delivering personalized content for every visitor, along with the predictive power of AI from Adobe Sensei
Uberflip (ABM): engage using natural language processing, it analyzes the content in your library and recommends the most relevant content to stakeholders based on their interests and preferences. It's important to note that you'll need to combine it with Hubspot, Marketo, Pardot, or Eloqua to store the stakeholders' journey analytics data.
PathFactory: identify which content is resonating most with their audience and provide personalized content experiences for each. See how each stakeholder has engaged with your content, channel, topic, or content type.
Note: you may find that these are already being used by your marketing team. These AI-powered tools can help Analyst Relations leaders optimize their content and messaging for maximum engagement and impact.
Identify which content resonates, generate recommendations for improved engagement, and set them onto automated engagement journeys.
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