Use AI to CRUSH the competition, delight customers + finding purple squirrels
Knowing what your rivals are doing is useless if you can't out-execute them.
Thanks for reading AlphaEngage issue #102. Read past issues.
Inside: AI-powered competitive intelligence, customer service automation, and hiring the right AI lead.
SALES & MARKETING
You’re [Probably] Doing Competitive Analysis Wrong.
Listen up, because this is important: If you don't know what your competition is up to, you're leaving your business vulnerable to surprises that could cost you big time.
Sure, your sales team might butter you up with the same old "We do run into Company XYZ from time to time, but our product is far superior," but can they prove it?
Has anyone here read their latest press releases? Product specs? Case studies? User reviews? Do we know where their product has been featured? What about the ads they're running on Google and LinkedIn?
You have to be on top of this stuff and, obviously, we’re going to tell you that AI can help.
With AI-powered competitive intelligence tools, you can automagically collect and analyze data from every corner of the Internet, uncovering key insights that give you a real-time view of the competitive landscape. We're talking...
Product updates and pricing changes
Shifts in marketing strategies and ad spend
Changes in market share and customer sentiment
Emerging industry trends and disruptive technologies
Armed with this knowledge, you can make informed decisions rather than assumptions, adapt your strategies and tactics on the fly, and stay one step ahead of the competition, rather than the other way around.
How do you harness the power of AI for competitive intelligence? Put someone in charge of it and follow these steps:
Step One: Define your objectives and identify your top competitors based on market share, product offerings, and target audience. This will help you focus your efforts and ensure that you're gathering the most relevant and actionable insights.
Step Two: Evaluate and select the appropriate AI-powered tool(s), taking into account factors such as data sources, insight accuracy, and scalability. Here are a handful of popular AI-powered competitive intelligence tools:
Crayon: Tracks competitors' digital footprints across websites, social media, and more, providing real-time insights into their strategies, tactics, and customer sentiment.
Klue: Combines AI-powered data collection with human insights to deliver actionable competitive intelligence that drives informed decision-making and strategic planning.
Kompyte: Monitors competitors' online presence, including websites, social media, and news mentions, alerting you to key changes, trends, and potential threats or opportunities.
Contify: Delivers customized competitive intelligence reports by leveraging AI to gather and analyze data from a wide range of sources, helping you stay ahead of industry trends and disruptive technologies.
SimilarWeb: Provides in-depth insights into your competitors' online performance, including website traffic, engagement metrics, and marketing strategies, enabling you to benchmark your performance and identify growth opportunities.
Step Three: Integrate the tools into your existing tech and marketing stacks, which may involve IT setting up API connections, data feeds, and ensuring compatibility with your other tools. Proper integration is crucial for seamless data flow and maximum efficiency.
Step Four: Train your teams and establish best practices for sharing competitive intelligence across the organization. This is where collaboration comes into play. Ensure that your sales, marketing, and product development teams are all informed, sharing insights and aligning strategies and tactics based on the latest competitive landscape.
Everyone in the org has a role here...
C-suite - Strategic planning and resource allocation
Sales - Refining tactics and boosting win rates
Marketing - Optimizing messaging and campaigns
Product - Prioritizing features and innovating
IT - Running the tech
Step Five: Measure and adjust accordingly based on key metrics, such as win rates, market share, and customer satisfaction. Continuously monitor these KPIs and make data-driven adjustments along the way—tweak the AI tool's configuration, improve messaging, adjust ad spend, optimize customer outreach, and take any other necessary actions to counter the competition accordingly.
Go get ‘em!
AI IN ACTION
Chicken So Tasty
Problem: Chick-fil-A faced challenges in maintaining food quality, minimizing waste, and proactively identifying potential foodborne illness outbreaks across its locations.
AI Solution: Chick-fil-A implemented two AI-powered solutions. First, an IoT (Internet of Things) system utilizing cameras, edge computing (processing data closer to where it's collected), and analytics to monitor the freshness of hot food and alert staff when items need to be discarded.
Second, an NLP-powered (Natural Language Processing) AI application that monitors social media for mentions of food poisoning, analyzing sentiment and legitimacy using Amazon’s AWS Comprehend.
Results: The AI solutions led to improvements in food quality, waste reduction, and proactive identification of potential foodborne illness incidents, helping to protect customer health and maintain the company's reputation.
CUSTOMER SERVICE
The More You [Will be Required to] Know...
Advancements in AI are happening at speeds most of us have never experienced before—faster than the Internet initially grew, cell phones, social media, or that really fast superhero, Flash.
To keep up, you’ve got to start testing, learning, and deploying AI solutions across the organization—especially for customer-facing functions, where expectations will be super-high.
Get to know these 10 AI-powered customer service strategies already being used by loads of companies...
Chatbots: AI-powered chatbots can handle simple customer queries 24/7, reducing response times and freeing up human agents for more complex issues.
Personalization: AI can analyze customer data to provide personalized recommendations and experiences, enhancing customer satisfaction and loyalty.
Sentiment Analysis: AI can detect customer sentiment in real-time, allowing agents to prioritize and respond to dissatisfied customers promptly.
Predictive Analytics: AI can predict customer behavior and preferences, enabling proactive customer service and targeted marketing efforts.
Automation: AI can automate repetitive tasks, such as data entry and ticket routing, improving efficiency and reducing human error.
Knowledge Management: AI can help organize and retrieve relevant information from knowledge bases, empowering agents to provide accurate and consistent responses.
Language Processing: AI-powered natural language processing (NLP) enables the understanding and response to customer inquiries in multiple languages, thereby expanding the global reach.
Fraud Detection: AI can identify and prevent fraudulent activities, such as account takeovers and suspicious transactions, protecting customers and businesses.
Performance Monitoring: AI can track and analyze agent performance, providing insights for training and process improvements.
Augmented Agents: AI can assist human agents by suggesting responses, retrieving relevant information, and handling simple tasks, enhancing agent productivity and customer experience.
“Woah! Where do I start,” you ask?!?😯
Chatbots and automation should be your top priorities. Chatbots can handle a large volume of simple customer inquiries 24/7, providing quick responses and allowing your human agents to focus on more complex issues. This not only improves customer satisfaction but also increases efficiency.
To get started, identify the most common customer questions and develop a chatbot that can effectively address them while ensuring a smooth handoff to human agents when necessary. Customers already expect this stuff!
Automating repetitive tasks, such as data entry and ticket routing, is another key area where AI can make a significant impact. By streamlining these processes, you can reduce the risk of human error and enable your agents to focus on high-value tasks that directly impact the customer experience.
Begin by analyzing your current customer service processes to pinpoint areas where automation can be applied, then select the appropriate AI tools that integrate well with your existing systems. Don't forget to provide adequate training to your agents, so they can work seamlessly with these new tools.
As you progress, you can explore other AI applications, such as personalization, sentiment analysis, and predictive analytics, to further enhance the customer experience and stay ahead of the curve.
HR
Finding the Purple Squirrel
Let’s say for a moment that you love❣️this newsletter and read it every week. And let’s say that all of the various ideas, usually broken down into business cases or departments, are all things you want to be doing or at least digging into further.
What does that job description look like? Does it even exist? Or is it a true purple squirrel?
First, it’s not realistic to expect this person to understand every facet of every department (sales, marketing, IT, customer service, etc.). Nor is it realistic for this person to be on the front lines of the technical implementation of AI solutions, such as coding or API integrations.
Also, be careful with your standard requirements—college ain’t what it used to be (yeah, we said it). And nobody has 15+ years of experience implementing AI to the degree we’re talking about here.
What you do want is a smart, strategic, analytical thinker, problem-solver, and innovator. Someone who can think outside the box after diving into the data and analytics to find gaps and opportunities where AI can solve problems, save money, make money, increase productivity… the list goes on.
Here’s some copy you can use:
The AI Strategy and Implementation Lead is responsible for driving the successful adoption and optimization of AI technologies within the organization. This includes:
Conducting a comprehensive assessment of the organization's goals, processes, and tech stack to identify areas where AI can be most effectively utilized, ensuring that AI initiatives align with business objectives and deliver measurable value.
Developing a strategic roadmap for AI implementation that outlines key milestones, resources, and timelines, taking into account organizational readiness, budget, and potential risks.
Evaluating and selecting third-party AI solutions that best fit the organization's needs, considering factors such as scalability, integration with existing systems, and vendor support.
Leading cross-functional teams in the implementation of AI systems, fostering collaboration between technical and non-technical stakeholders, and ensuring smooth integration with existing processes and workflows.
Monitoring AI performance using established metrics and KPIs, and establishing AI governance frameworks that address data privacy, security, ethics, and compliance issues.
This role requires deep technical knowledge of AI technologies, governance, and ethics, as well as strong project management skills to oversee AI initiatives from ideation to implementation.
The AI Strategy and Implementation Lead should also possess excellent communication and presentation skills to effectively convey complex AI concepts to diverse audiences, as well as strategic thinking capabilities to align AI initiatives with organizational goals and drive business value.