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To measure a smartphone/brand’s performance look beyond the shipments metric

by Abishek.CConnectivity, CX, Telco & ICT

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One question I’ve often been asked is – “How do you measure a smartphone (model / brand’s) performance or success?”

There are many metrics by which a smartphone’s (model / brand) performance (or success) can be measured; the most common of them being the unit shipments

Quick note: Different entities (Carriers, brand, retailers, etc.) & teams within (procurement, marketing, pricing, channel ops, etc.) the smartphone’s value chain will have different goals and as such will adopt variations of device performance metrics that best suit their needs

The post takes a generalized view on key smartphone metrics (beyond shipments) that help in constructing one such holistic performance picture (device standpoint)

First Step

1. Shipments

Shipments metric is typically the first measure that comes to mind when comparing, ranking or evaluating any smartphone / brand’s performance

This metric, for the most part represents the number of finished smartphones that have been shipped out

But…

As with any other one-dimensional metric, shipments too would require companion measures to provide clearer context to smartphone performance & comparisons

Also, shipments is only the first stage in a modern smartphone’s lifecycle (particularly flagship & iconic models)… it’d be equally important to augment key post-shipment measures if the device’s holistic performance is being sought

Hence shipments metric by itself is simply the first step in determining a smartphone’s holistic performance

Post-shipment Measures – Questions & Metrics

Exploring questions at key post-shipment stages of a smartphone’s lifecycle…

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…correlating to measures under 3 key categories –

  • True Device Sales (Volume)
  • Device Lifetime Revenue (Revenue)
  • Device Engagement & Loyalty (User)

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True Device Sales

Where shipments doesn’t translate into (1:1) ‘sales’, the following metrics could help derive the true device sales measure

2. Channel Point Of Sale (POS) Sell Through

Sell Through metric represents the number of smartphones that have sold through to the end-user (e.g. via channel POS)

The Sell Through metric paints a clearer sales picture (vs. shipments alone) and also provides a view into channel inventory (read: shipped BUT unsold devices)

3. End User Activation

This metric paints a more accurate picture of true sales, derived from the first time device activation by the end-user

The User Activation metric is also helpful in measuring true sales performance in scenarios (or markets) where the device may pass through multiple POS sell-through layers (e.g. bulk purchases, individual retailer / re-seller, etc.)

May also factor in: Returns / Recall rate

  • If deemed significant enough, device returns & recalls could also be factored into the final true sales performance measure

  • Device Lifetime Revenue

Revenue metrics when augmented with Volume metrics provide the 2nd dimension of a smartphone’s holistic performance

  • 4. Net Device Margin

  • This metric provides the Device Margin = Device Selling Price + OEM ancillary revenue – Costs 
    • Device Selling Price: SP per device to the OEM (may be substituted with ASP – Avg. Selling Price) 
    • OEM Ancillary Revenue: Applicable to OEMs who also offer branded ancillary products & services (think: branded accessories, content, etc.) AND if the smartphone has directly contributed towards revenue from the same 
    • Device Costs: Per device-associated costs (e.g. subsidies, logistics, acquisition, marketing, commissions, etc.)

5. Ancillary & Attachment Revenue

Select smartphones have a unique potential to generate higher ancillary & attachment revenues than others (think: model-sepecific higher tariff plans, accessories, App spend, device protection add-ons, etc.)

This revenue metric (in part) measures this potential; particularly for its value chain partners (Retailers, Wireless Carriers, et al.)

6. “2nd Life” Revenue Potential

Select smartphones (particularly flagship & iconic models) preserve their value well beyond their ‘primary life’… 

…and as such are re-purposed by Carriers & Retailers to generate extended revenue from this 2nd Life (think: refurbished, certified preowned Post/Prepaid, etc.)

This metric when integrated with associated Net Margins, Price Erosion & related CLV metrics provide a smartphone’s lifetime revenue potential measure (DLR – Device Lifetime Revenue)

Device Engagement & Loyalty

7. Satisfaction / Loyalty

This metric(s) represents the user satisfaction & loyalty with their smartphone and could be a result of the various device / OEM attributes (e.g. UX, UI, pricing, OS features, updates, etc.)

This metric could also be correlated to device experience / engagement / abandonment measures and forms one of the base inputs into predictive modeling of repeat & ancillary purchases

This metric could be derived from a combination of device usage analytics including Apps, content, social media listening / analytics, post-activation surveys, promoter / detractor scores measure, et al.

Device engagement & satisfaction metrics also provide a valuable indication (read: potential driver) of future sales & revenue (x-sells, up-sells, BBTIU, etc.)

Holistic Performance

Together, the aforementioned metrics (or combination thereof) provide a more holistic view of smartphone performance as opposed to shipments alone

These measures may also be weighted according to their importance / requirements to the various value chain entities, teams, local market conditions & statistical model being sought

Using holistic performance overcomes the 1-dimensional shortcoming of using shipments alone… and enables a more leveled comparison between smartphones (models & OEMs), irrespective of their focus on volume or high margin

So… 

So to answer the question – how do I view a smartphone’s performance?
From its holistic performance indicator (including measurable & subjective metrics) over its lifecycle… well beyond the initial shipments metric

As with any statistics / research it is equally important to assess the accuracy & confidence levels of each of the metrics’ underlying data sources (OEM reporting, component supply chain, retailer POS systems, App installs, surveys, et al.), assumptions and models

Similar concept also applies to IoT categories that rely on ongoing service revenues & user engagement in addition to initial hardware sales (more on this topic in a separate post)

Stay tuned!

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