Overview
This post is an extension of our previous post, Ideal Product Category for AIPR, which is one of the core “so what” strategic implications of AIPR.
We will explore what type of client industries may generally be a good candidate to invest resources into developing an AIPR strategy, as well as other general characteristics of company or industry traits that may also indicate so.
Opportunity
Belief in AIPR
Natural AIPR Fit
Firstly, the product category for which the client sells in has to be a good natural fit for AIPR as per the characteristics outlined in the previous post.
In short, these characteristics are:
- AI Search Volume Potential
- Decision Narrative Richness
- Constraint Type Diversity
- Meaningful Differentiation
- Decision Consequence
A product category does not have to meet all of this criteria necessarily, but it should be aligned well overall.
Economic Benefit
Having a clear sight to economic benefit from AIPR would make the product category a good candidate.
Below are some key ways that can be seen, though kept minimal for simplicity.
Afterall, there are many different ways that an AIPR can show ROI for the brand. Immediate profitability is one of the most obvious signs.
Revenue Potential
Average Sale Price (ASP)
Let’s say that shoes and laptops both have a similar level of decision narrative richness, AI search potential, and other factors the same.
What is the ASP of a shoe? Perhaps $100? Compared to a laptop, it may be closer to $500.
Given the same AI search volume potential, laptop could be the better category for seeing ROI on AIPR strategy.
Here, the more accurate label would be average profit potential, but that type of data tends to be less publicly available than sales price, so for simplicity, we will keep the label as ASP.
Customer Lifetime Value (CLV)
If the CLV of onboarding one customer from AIPR is great, this would be a meaningful economic benefit from AIPR.
Market Size
Market size actually overlaps with AI Search Volume Potential, but nonetheless, it is the simple question of whether or not the market is big enough that AIPR strategy should be set.
Return on Investment (ROI)
Revenue potential – cost to implement = ROI
Move the Needle
Sure, AIPR strategy may have economic benefit – but how much is this moving the needle at the end of the day?
How about in the future? Do we think AIPR is worth investing into now? Do we think AIPR will move the needle tomorrow?
Competitive Pressure
The client is either currently at the top recommendation position in AIPR, or is occupying another spot in the gap analysis.
Current AIPR Position
The higher the AI search volume, the more the AIPR position matters.
If there is a lot of search happening in the category, they will want to act now, not later.
Not in Top Position
Clients who are not currently at the top position may have a more urgent incentive to develop an AIPR strategy to overthrow the current top position holder.
Current Top Position
If the client is currently at the top position feels competitive pressure, they may want to:
- Put a moat around their throne to make it more difficult for the second, third, or the fourth contender to catch up.
- Have a radar that can show what competitors are approaching and how fast.
If competitors are working with Narr Theory, the threat of catching up would be greater.
Feeling The Pressure
The higher the belief in AIPR, the greater the AI search volume potential, and the more competitive a client, the competitive pressure to take action will feel stronger.
The More the Merrier
In a way, product categories where there are abundant alternative options may be a great client for AIPR. Because a new running shoe entering the market, if recommended by AI all over the world, this heightens the motivation for the company to pursue such a market tactic. This is not to say the potential is “the more the merrier” 100% of the time, but there may be cases where this is exactly true. Because AI tends to recommend one single product as its top recommendation. Though each token may give a slightly different recommendation each time, ultimately, this can be seen as having a top recommendation per each target narrative, which is very powerful.
Feasibility
Achievable Goal – “In the Pocket”
If the client and their team members see the value in AIPR, but feel they are “out of pocket”, as in they are too out reach to make a significant move, they may not feel compelled to act on it.
Although this may be a tempting feeling to sit on, this may become highly detrimental for them if the product category is ideal for AIPR – millions of customers will be searching for their products, while they are not even mentioned.
Resource Alignment
What resources and/or internal department members are needed to action on AIPR strategy? Do we have all the necessary components?
If not, how can an expert like Narr Theory help us prepare?
Evidence Creation Potential
This is actually a part of AIPR strategy and action plan, but it’s worth noting here.
Does the client have the readiness or willingness to become ready to create evidence for AI?
This is influenced by their overall belief in AIPR, the internal stakeholders like department managers, executives, and the “head of the snake”, the CEO or the owner directing the team.
Adoption
Stakeholder Alignment in AIPR
AI Product Recommendation (AIPR), even the term itself may be new for many clients.
That being said, it is possible that some clients may have started to think of similar ideas on their own. The higher their own adoption of AI in questions, the more likely.
Nonetheless, if the stakeholders are not bought into why AI matters for product discovery going forward, they will not be able to agree on investing into an AIPR strategy, no matter how good their product category’s natural fit to AIPR may be.
Risk Tolerance
No matter how you see it, AIPR is a new concept, let alone investing into an actionable AIPR strategy.
Even though some people may be more open to the concept due to their familiarity with SEO, it does not mean that they may be one of the first among their peers to formally invest resources into an AIPR strategy.
That being said, the more solid the belief in AIPR’s potential is, the more willing they may be to take on the risk to be one of the first to take an action.
That being said – what are the implied risks from allocating financial resources into AIPR?
The risk would be generally in either:
- a) Proposed uncertainty reduction does not happen – clients stay at the same level of uncertainty
- b) Executed action plan does not influence the AIPR position
Especially for the very first time client of Narr Theory, this could be a tough risk to take on.
For this reason, Narr Theory is building a separate case study category to publicly share all the hypothesis observations and repeat experiments to help clients see proof first hand.
Budget Allocation
Like all enterprise projects, there needs to be a budget allocated to it.
AIPR is new, so it is doubtful that companies will have a readily accessible budget for “AIPR”
However, it covers:
- Product Discovery – which is a part of marketing and SEO, etc.
- Sales
- Product Development – R&D potentially
- Enterprise Strategy – CEO & Management
It is possible that this topic may catch the attention of executives from these departments.
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