Heads of Sales

Volume matters, but only once quality is defined in terms your sales team actually recognises: firmographic fit, buying-stage signal, and evidence of genuine intent rather than a downloaded whitepaper from someone doing research for a university assignment. We build lead scoring and qualification criteria with your sales team in the room, not in isolation, because a scoring model built by marketing alone tends to reward the behaviours that are easiest to track rather than the ones that actually predict a closed deal.

We also report on pipeline the way a sales leader reports on it: by stage, by source, by rep, and by the conversion rate from each stage to the next, rather than by top-of-funnel volume alone. That means we're accountable for the same number you're accountable for in your own leadership meetings, which changes how a lead generation programme gets built from day one.

In practice this means we'll happily reduce the raw volume of leads if it improves the qualified pipeline that actually reaches a proposal stage. A campaign that generates fewer, better-fit leads and a higher win rate is a better outcome than one that inflates the top of the funnel and leaves your team to do the filtering manually.

Most marketing-to-sales SLAs exist as a slide from a workshop eighteen months ago that nobody has looked at since. We build SLAs that are specific enough to be operational: what counts as qualified, how quickly a lead must be worked once it's assigned, what happens when a lead is rejected and why, and how disagreements get resolved without turning into a monthly stand-off between department heads.

Each SLA includes a documented handoff process — the exact data a rep receives with a lead, the context they need to open a conversation intelligently rather than cold, and a feedback loop that routes disqualification reasons back to whoever built the campaign, so the targeting improves rather than repeating the same mismatch every quarter.

We review these SLAs on a set cadence, typically monthly in the first quarter and quarterly after that, because a good SLA is a living agreement, not a document you sign once and never revisit. Markets shift, ICPs get refined, and an SLA that doesn't flex with them quietly stops being followed.

We build sales collateral from the same discipline we apply to positioning work: interviews with your top-performing reps about what actually lands in a live conversation, review of won and lost deals, and a clear map of the objections that recur most often at each stage of the funnel. Decks built this way survive contact with a genuinely sceptical buyer, rather than reading well in a workshop and falling apart on a call.

Typical outputs include a core sales deck mapped to buyer stage, one-pagers for the specific objections your reps hit most often, a competitive battlecard naming the alternatives your prospects are actually comparing you against, and case study formats built for the two or three sectors where you win most consistently.

None of this is static. As new competitors emerge or a pricing objection starts showing up more often, we update the relevant asset rather than letting the whole deck slowly drift out of date until someone finally notices in a QBR.

A forecast is only as reliable as the data underneath it. We audit stage definitions, required fields and source attribution across your CRM, then fix the structural issues that make pipeline reporting unreliable: duplicate records, inconsistent stage progression rules, and campaigns tagged so inconsistently that nobody can say with confidence which channel actually influenced a closed deal.

For multi-touch B2B sales cycles, single-touch attribution is close to useless — a deal that closes six months after an outbound call, two content downloads and a paid retargeting sequence didn't come from one channel, it came from all of them working together. We set up attribution models that reflect this reality rather than crediting whichever channel happened to be last, which typically overstates the value of bottom-funnel activity and understates everything that built the pipeline in the first place.

Once the data is clean, we build the dashboards your leadership team actually looks at: pipeline by source and stage, conversion rates between stages, and forecast accuracy tracked over time so you can see whether the number you're presenting to the board is getting more or less reliable each quarter.

Outbound and inbound solve different problems and most sales leaders end up under-resourced in one of them. Outbound gets you into accounts that fit your ICP precisely but have never heard of you; inbound captures demand from buyers already searching for a solution but gives you no control over which accounts show up. Relying on only one leaves obvious pipeline on the table.

We typically build a blended approach: targeted outbound sequences into named accounts that match your ideal customer profile, supported by content and paid media that keep those same accounts warm across multiple touchpoints, alongside inbound SEO and content built to capture buyers already searching for the category. The two motions should reinforce each other — a prospect who's received a well-timed outbound message is far more likely to convert on a landing page they find later through search, because the name is already familiar.

Sales cycle length is one of the clearest signals of whether marketing and sales are actually working as one system. When it's too long, the cause is usually upstream of the sales conversation itself: leads entering the pipeline too early, weak qualification letting unready buyers through, or collateral that doesn't answer the objections that stall a deal at proposal stage.

We shorten cycles by tightening qualification criteria so reps spend time on genuinely ready buyers, building nurture sequences that do more of the early education before a rep ever gets involved, and equipping reps with the specific content that answers a late-stage objection immediately rather than requiring a follow-up call two weeks later that gives the prospect time to lose momentum or start talking to a competitor.

We track this explicitly, stage by stage, so we can show which part of the cycle actually got shorter and why, rather than presenting a single headline number that could be explained by a dozen other factors.

A CRO presenting a forecast to the board needs more than a pipeline total — they need confidence in the assumptions behind it: realistic conversion rates by stage, an honest read on deal risk, and pipeline coverage that reflects actual historical win rates rather than an optimistic multiple picked because it looks good on a slide.

We work with your revenue operations function, where one exists, or directly with sales leadership where it doesn't, to build forecasting models grounded in your own historical data rather than generic SaaS benchmarks that rarely apply to your specific sales motion. That includes flagging pipeline that's stalled or overdue for its stage, so it gets addressed before it quietly wrecks next quarter's number.

The goal is a forecast that survives scrutiny in a board meeting, because it's built on definitions, data and cadences that were agreed and tested in advance rather than assembled the week before the meeting.