Most companies that try to crack Asia Pacific make the same mistake. They take what worked in the US or UK, translate the collateral, hire someone in Singapore, and wait for the pipeline to come in biut it doesn’t.
The problem isn’t the market. It’s the assumption that the go-to-market that won at home is the go-to-market that works here.
Chris Perrine has spent 30 years figuring out the difference. He founded Springboard Research in Singapore in 2003 and sold it to Forrester. He ran monetization at Product Review in Australia. And then he joined G2 as the company’s first employee in Asia Pacific, building the regional business from a home office to a team spanning Singapore, India, and Australia.
In a recent episode of the B2B Sales Blueprint, he shared what those 30 years actually taught him about B2B sales strategy for APAC: localizing go-to-market, building AI-powered sales teams, and why the way buyers research and choose software is changing faster than most sellers realize.
Here’s what stood out.
The mindset shift: your GTM is the starting point, not the answer
The single biggest mistake companies make when entering APAC is treating their existing go-to-market as the finished product rather than the starting point.
When Chris Perrine joined G2 to build out APAC, there was no budget and no team. Just him in a home office in Singapore, figuring it out. He spent the first four months doing everything himself: prospecting, running demos, closing deals, onboarding customers.
He was BDR, AE, and CSM simultaneously.
He calls this the “grow slow to grow fast” approach. Rather than hiring a team upfront, he used that period in the field to learn what actually resonated with APAC buyers – and what didn’t.
“I had to understand everything. I had to know the product, the processes. That’s where the positioning and messaging came from.”
One of the first things he realized was that G2’s US messaging didn’t land. In the States, the pitch centered on getting on the G2 grid, building category presence, and being discovered by buyers. In APAC – specifically India and ANZ, which became G2’s two primary markets in the region – buyers wanted something different.
“India and ANZ were our big markets because that’s where VC money was pouring in for companies wanting to go global. So our messaging became: we’re going to help you grow in the US.”
That shift sounds simple. But it required being close enough to the market to hear it. You can’t make that call from head office.
What most companies get wrong in their B2B sales strategy for APAC
Most APAC expansions fail not because the market is wrong, but because the company over-replicates or over-localizes – and has no framework for knowing the difference.
Chris Perrine’s answer to this is what he calls the 80/16/4 rule.
The 80/16/4 rule for GTM localization
When you take go-to-market into a new region, the framework works like this:
- 80% stays the same: positioning, product fundamentals, sales process, core ICP
- 16% (the remaining 20%, of which 80% should look similar): light adaptations such as pricing adjustments, regional messaging tweaks, or localized case studies
- 4% (the final slice): things that are just completely different for that specific market
“Japan is probably a lot different, maybe 60% the same. Australia maybe 85%. But I’ve always found it works, because US companies get it when you frame it that way. You can put something in a bucket and say: this is one of the 16.”
The value of naming the framework is practical: it gives you a way to have the localization conversation with head office and get buy-in for the changes you actually need. Instead of arguing about whether something should change, you’re agreeing on which bucket it sits in.
The other consistent mistake companies make in their B2B sales strategy for APAC: they want immediate scale. They hire before they understand the market, set quotas based on US or European benchmarks that don’t account for market maturity, and pull headcount before the business has had time to breathe.
“The teams in the States need to give you a lot of trust. And you need a consistent process. But keep innovating – what works today might not work tomorrow, and what works in the States might not work here.”
How reviews actually work in a sales cycle
B2B reviews are primarily a sales tool – not a marketing one – and the CROs who treat them that way see measurably different outcomes from those who leave reviews in the marketing stack.
Chris Perrine spent seven years running G2’s APAC business. His most contrarian view: reviews do their best work inside a sales cycle, not at the top of funnel.
“I’ve been a big believer that reviews are better for sales than they are for marketing. Sales teams don’t come to reviews naturally – it needs the CRO to really push it.”
The mechanism is buyer stress. When someone is evaluating software, they’re not just deciding whether it works – they’re deciding whether to put their reputation on the line. For a champion trying to get internal buy-in, the risk is real.
“Buyers are stressed. They’re putting their reputation on the line. They’ve got more riding on it than you do.”
Reviews reduce that stress. When an AE can point to a customer who had the same use case, the same company size, and the same implementation challenges – and came out the other side successfully – that’s not marketing collateral. That’s a sales tool. The best AEs find the reviews that match the buyer’s specific context and send them as follow-ups.
Chris’s analogy from his Forrester days:
“We didn’t sell research. We sold insurance. That CIO is basically saying: if this doesn’t go well, at least I can say the analyst said it was good.”
How AI has changed the role of reviews in buyer discovery
There is a second layer to this that goes beyond the sales cycle: how LLMs are changing the way buyers find vendors in the first place.
When Chris started at G2, the typical buyer journey began with a broad Google search, a click on a blue link, and a landing on a G2 category page. About 70 to 80% of G2’s traffic came directly from Google.
That’s shifted. Buyers are increasingly running conversational searches through LLMs: “what’s the best marketing automation software for a mid-market retailer in Australia” rather than “best marketing automation.” When they do, those LLMs pull from review platforms as a trusted source.
“G2 was, I think, the 7th or 8th overall contributor to OpenAI – not just tech, but across everything. Because so much software research had shifted to the LLMs.”
What this means in practice: vendors with reviews tagged to specific verticals, use cases, or geographies are surfacing in AI-generated outputs in categories where they couldn’t previously compete on Google organic. A niche manufacturing CRM vendor – buried behind Oracle and Salesforce in organic search – can appear at the top of an LLM result because their G2 reviews are consistently tagged for the manufacturing segment.
The buyer signal has moved. The question is whether your review strategy has moved with it.
Building an AI-powered sales team from scratch
When Chris Perrine scaled G2’s SMB business to a 30-plus person team in India, he found that AI’s biggest impact wasn’t efficiency – it was giving junior reps the credibility to sell to senior buyers.
About 18 months before leaving G2, Chris took over the company’s global SMB business and moved it to India, hiring 30 to 35 people – mostly 25 to 26-year-old AEs with limited sales experience.
He organized the team’s AI usage into three buckets:
- How do you increase efficiency with what you’re already doing?
- What can you do with AI that you just couldn’t do before?
- Can AI fundamentally change the ratio of output to headcount?
Bucket two was the one where he saw the most success.
What worked: the post-discovery AI report
The highest-impact initiative was using Dust – an AI agent tool built on top of Anthropic and OpenAI, plugged into Salesforce, Snowflake, and Gong – to generate post-discovery call reports automatically. An AE would finish a call, link the Gong recording, and receive a 10-page report within four to five minutes covering the prospect’s G2 visibility, competitive position, and recommended next steps.
The impact was credibility, not just speed.
“A 25-year-old AE is selling to a 45-year-old CMO and doesn’t have that experience. What this did is build a lot of content for them to use. We saw our conversion rates skyrocket.”
Instead of sending a generic follow-up summary, the rep could open with: “Following our call, I put together this report on your AI visibility with G2 and how you compare to your top three competitors.” That’s a different kind of conversation.
What worked: AI-powered call coaching at scale
They also used AI to run call coaching across the whole team simultaneously – setting a monthly theme (objection handling, call structure, discovery quality) – running every rep’s Gong calls through an LLM, and generating individual coaching reports that managers used in 1:1s.
“That’s a massive unlock. How many calls can you actually listen to?”
Previously, a manager might review two or three calls a week. With AI, the entire team was being analyzed and coached on the same theme at the same time.
What didn’t work: data confidence and adoption
Two things held the program back. First, hallucinations. Even with a well-configured tool like Dust, every report required human review before it went out. Chris describes regularly finding reports that referenced data from months earlier: “This report stopped in October. We’re in January.”
Second, adoption resistance. Despite rolling out tools that demonstrably saved time, some reps didn’t use them for months. One AE in India admitted she’d been afraid of the tool from May through November before finally starting to use it – then immediately called it a game-changer. “It was almost like they had to live the pain before they’d use the solution.”
His practical advice for sales leaders overwhelmed by the pace of AI change: set a daily reminder to think about it.
“Some days it was literally just a couple of minutes. But it kept me from just grinding through tasks I knew I could do in 10 minutes – and asking myself: could I build something here that I never have to do again?”
How to apply this to your revenue team
- Audit your APAC messaging before your next hiring cycle.
Don’t hire a country manager and hand them US collateral. Before you expand, talk to 10 to 15 buyers in the region – or review your lost deals – and identify where the message isn’t landing. Use the 80/16/4 framework to decide what needs to change and brief your head office accordingly. - Make someone in your team responsible for reviews, and make it a sales motion, not a marketing one.
Reviews work best when AEs use them situationally – finding a review that matches the buyer’s use case or segment and using it as a follow-up. That behavior needs to be modeled and coached, not just encouraged. If your CRO isn’t actively pushing it, it won’t happen. - Angle your reviews towards the niches you want to win.
LLMs are reading review sites and using specific tags – industry, use case, company size, country – to answer conversational search queries. If your reviews don’t mention the verticals or geographies you’re targeting, you won’t show up in those outputs. Coach customers to be specific when they write reviews. - Go slow before you go fast in a new market.
If you’re building in a new region, resist the urge to hire a full team before you’ve done founder-led (or leader-led) sales. Spend time in the market. Close the first deals yourself. The insights you’ll get from doing that – about messaging, about objections, about what buyers actually care about – are worth more than the six months of output you’d get from a rep you haven’t briefed properly. - Start your AI program with one use case that generates a visible output.
The post-discovery report is a good example. It’s concrete, it’s fast, and it produces something the rep can point to. Once the team sees a conversion rate improvement attached to a specific tool or workflow, adoption follows. Starting with efficiency gains (saving time on admin) tends to land less well than starting with outcomes (more deals closing). - Build individual coaching into your AI rollout, not just team-level insights.
Using LLMs to analyze individual call performance – theme by theme, rep by rep – and deliver personalized coaching plans changes the manager-to-rep ratio. This is where the real capacity gains come from. But it requires discipline: a monthly theme, consistent data inputs, and managers who are trained to use the output in 1:1s. - Don’t wait for the AI tools to be perfect before you start.
Hallucinations are real. Data freshness is a problem. Reviews are required. But the answer isn’t to wait – it’s to build review into the workflow from the start. The reps who were reviewing AI outputs before sending them were still saving significant time and getting better results than those who weren’t using the tools at all. - Treat AI adoption as a culture question, not a training question.
The reps who didn’t adopt AI tools weren’t lacking information – they were afraid. The fix isn’t more onboarding documentation. It’s leaders modeling the behavior, sharing wins publicly, and making it normal for a 25-year-old AE to send a 10-page competitive report after a discovery call.
Conclusion
The through-line of everything Chris Perrine has built and sold and led in APAC is a specific kind of discipline: the willingness to start from scratch when the situation calls for it, to resist the assumption that what worked elsewhere will work here, and to keep adapting when it doesn’t.
That applies to GTM localization, where the instinct is to replicate rather than reinvent. It applies to AI adoption, where the instinct is to wait until the tools are proven rather than learning while building. And it applies to how you use buyer validation – reviews, reference calls, case studies – which most sales teams treat as marketing output when they’re actually one of the highest-leverage tools in a rep’s kit.
APAC isn’t a smaller version of a Western market. It’s a collection of different buying cultures, growth stages, and commercial contexts that reward operators who’ve taken the time to understand them. The companies that win there tend to be the ones that send people into the market before they send strategies.
Listen to the full podcast episode.
Frequently asked questions about B2B sales strategy for APAC
The 80/16/4 rule is a GTM localization framework developed by Chris Perrine based on his experience building revenue teams across Asia Pacific. It states that 80% of your go-to-market should remain consistent across markets (core positioning, product fundamentals, sales process), 16% should look similar with light regional adaptation (pricing, messaging nuance, local references), and 4% may need to be completely different for a specific market. The framework is designed to help revenue leaders make the case for localization to US or global head offices without having to rebuild the GTM from scratch
According to Chris Perrine, former VP APAC at G2, reviews are more valuable as a sales tool than a marketing one. While reviews drive top-of-funnel discovery, their highest-impact use is within the sales cycle – specifically as a tool for AEs to reduce buyer stress and support internal champions. Sending a review that matches a buyer’s specific use case, company size, or industry as a follow-up is more persuasive than generic category proof points
LLMs like ChatGPT and Gemini are replacing Google as the starting point for software research among B2B buyers. Searches are becoming more conversational and specific – for example, “best CRM for a mid-market manufacturer in Canada” rather than “best CRM.” LLMs pull from review platforms like G2 and Capterra as trusted sources, which means vendors with detailed, segment-specific reviews can surface in AI-generated results even when they can’t compete for organic search rankings against larger competitors.
One effective model, used by Chris Perrine at G2, involves setting a monthly coaching theme (such as objection handling or discovery quality), running all rep call recordings through an LLM, and generating individual coaching reports for manager-led 1:1s. This approach allows managers to analyze the entire team’s calls simultaneously rather than reviewing a handful manually. When combined with post-call AI reports that reps can send to prospects, the model has been shown to increase conversion rates and reduce the time managers spend on deal coaching.
Chris Perrine’s view is that AI will not reduce sales headcount in the short term. Instead, it will increase efficiency and may slow the pace of new hiring – companies may hire two or three people instead of ten. Whether that changes over a two-to-three year horizon depends on how fast the technology develops. The more immediate effect is that AI raises the floor for what a junior rep can deliver, giving less experienced sellers access to insights and content that previously required years of domain knowledge.
When asked in rapid-fire, Chris Perrine’s one-word answer was: curiosity. The supporting trait he identified for revenue leaders building in APAC specifically was entrepreneurial innovation – a willingness to keep adapting, because what works in one market or at one point in time often stops working as conditions change.
