Smart Upsell and Cross-sell Recommendations
Automatically identify complementary offers and upsell opportunities from customer context and sales history.
A sales rep reviews their portfolio on Monday morning with orders from the ERP, email threads, and whatever they remember from a recent site visit. Matching these sources rarely happens systematically.
Fasfox builds systems that cross-reference these sources to flag a concrete opportunity, with the data behind it, at the moment the rep prepares for a visit.
A sales rep’s Monday morning
Before heading out on his rounds, a sales rep reopens the ERP: two years of orders, quantities, renewal dates. He adds what he remembers from a site visit last month, an offhand remark about a line extension, a parts need mentioned over lunch. Matching these two worlds, the ERP’s structured records and what stuck in someone’s memory, mostly depends on what the rep happened to retain that day.
A pilot that only recommended the obvious
A first attempt built purely on order history produced a list of recommendations sales reps already knew: renew what renews every year. The two or three signals that would have justified a call, a site extension noted in a visit report, a contact change mentioned in an email thread, showed up in no CRM field at all. The pilot was judged useless and dropped within weeks.
A CRM that’s actually filled in
This kind of system only works if visit reports and sales conversations get recorded somewhere, even briefly, and if someone on the sales team owns keeping the offer catalogue current. Without that minimum discipline, the system will recommend what everyone already knew, and the project repeats the pilot’s failure.
A lead, never an outreach
We build a system that spots ageing orders, needs mentioned in correspondence, and offer combinations already sold together elsewhere, then ranks opportunities against the data that justifies them. The rep still decides whether to raise it: only they know the current tension with that account, an open dispute, a sensitive pricing negotiation that nothing in the history flags. The system never contacts the customer directly; it prepares the conversation and leaves the timing to the person who owns the relationship.