Customer Service
Cost to serve, repeat contacts and the root causes behind both.
Service operations generate enormous amounts of data and almost no insight. Contacts sit in the telephony platform, cases in the CRM, and the reason people got in touch nowhere at all. We join the contact to the customer and the order behind it, so cost to serve and repeat contact become measurable — and fixable.
The numbers that matter here
What we'd connect here
Whatever it is and however it exposes itself — API, database, nightly file, or a spreadsheet somebody maintains by hand. We only ever need read access, with personal data excluded.
What we do about it
Where it hurts
- Contact data split across phone, email, chat and social, with no single view
- Cost to serve unknown, so nobody can price or staff it properly
- Repeat contacts counted as new ones, hiding the real failure demand
- Agent performance argued from call listening rather than outcomes
What Acta builds
- One contact timeline per customer across every channel, joined to the order or account
- Cost to serve per contact, per customer and per product
- Repeat-contact and root-cause analysis, so failure demand is visible
- Deflection and self-serve impact measured against real volume
What you get
The reasons people contact you, ranked by what fixing them is worth.
Live in months rather than years, from £5k a month, on your own Google environment — handed over to you, or run by us.
Inside a customer service engagement
Service operations generate an enormous amount of data and almost no insight. Contacts sit in the telephony platform, cases in the CRM, chat and social in their own tools, and the actual reason a customer got in touch is captured nowhere consistent. So cost to serve is unknown, which means nobody can price or staff it properly, and repeat contacts get counted as fresh ones, hiding the failure demand underneath the volume.
We join every contact into one timeline per customer across phone, email, chat and social, tied back to the order or account behind it, in your own BigQuery. That is what makes cost to serve measurable per contact, per customer and per product, and it turns repeat-contact and root-cause analysis into something concrete: the product fault or broken journey generating a disproportionate share of your contacts stops being a hunch and becomes a ranked list. Deflection and self-serve impact get measured against real volume rather than against a vendor's claim.
The output is the reasons people contact you, ranked by what fixing each one is worth — so the roadmap argument is settled with a number. Cost per contact, first-contact resolution, repeat contact rate, average handling time and failure demand all read from one definition, and agent performance moves onto outcomes rather than call-listening.
Common questions
Can you tell us our real cost to serve?
Yes. We build cost to serve per contact, per customer and per product by joining the contact to the customer and the order behind it. Once it is measurable you can price and staff service properly instead of guessing at it.
How do you separate repeat contacts from genuinely new ones?
We join every contact into one timeline per customer across phone, email, chat and social, so a repeat contact is recognised as one rather than counted as new. That reveals the failure demand hiding in your volume — and its root causes, ranked by what fixing them is worth.
Can you measure whether self-serve and deflection actually work?
Yes. We measure deflection and self-serve impact against real volume rather than against a vendor's claim, so you can see what genuinely reduces contacts. Agent performance moves onto outcomes instead of call-listening anecdote at the same time.
Which customer service systems do you connect to?
Whatever you already run — it makes no difference whether a system exposes an API, a database view, a nightly file or a spreadsheet somebody maintains by hand. In customer service that usually means: Contact centre (Genesys, Five9, Amazon Connect); Ticketing (Zendesk, Freshdesk); Telephony and IVR; Workforce management; QA and call scoring. We only ever need read access with personal data excluded, and the layer is built in your own Google environment rather than ours.
Other sectors
Bring one decision your data should be helping you make.
30 minutes, no deck. We'll tell you on the call whether we're the right partner, and exactly what we'd ship in the first 30 days.