Tim Waring, founder and CEO of Netmonita discusses how brand owners may take
advantage of the upcoming technology
(printed in Product and Image Security Foundation No.182 July 2023)
Anti-counterfeit strategy is a relatively new area of business; 10 – 20 years for the majority
of active companies and a few decades old for a few of the earliest entrants. There are even
now very large businesses that have yet to start tackling counterfeits.
The companies involved in the fight are typically international with numerous staff in many
countries involved in tackling counterfeits with array of third-party suppliers across the
globe, including law firms and investigators to assist them. Sometimes dramatic raids take
place in the early hours with heavily armed police and large amounts of fake goods are
seized.
To date, anti-counterfeit efforts have typically been conducted discretely with a focus on
efficient and targeted removal of bad actors on and off line, like an immune system fighting
pathogens.
It feels for experienced, battle-hardened brands it is the end of a long first campaign with
some introspection of what is proving effective. Lessons have been learned from numerous
civil and criminal cases, working with law enforcement to stop key counterfeit sellers and
manufacturers, shutting down factories and seizing fake goods.
Here are a few key points that we have learned;
There is no suggestion of an end in sight.
Whilst these lessons indicate the difficulty of fighting counterfeits, this is not to say the work
has been in vain. The efforts over the years have led to significant disruption and made life
much more difficult for counterfeiters. They have had to come up with increasingly complex
methods of avoiding anti-counterfeit measures, reducing their profitability and deterring
other opportunistic entrants.
However, there is a problem anti-counterfeit professionals face within their own companies -
the benefits are often difficult to accurately quantify financially. When the wider business
looks in on anti-counterfeit metrics, they can be sceptical of what they are getting for the
spend.
The much larger traditional core business functions of operations, sales, marketing, finance
is where the budget for tackling counterfeits is generated and allocated. As such, the return
on investment is watched closely and when it is not always clear to assign a value to
successful outcomes the program spend can be questioned and be at risk of reduction. This
is despite of the wider problem of counterfeits being on the increase.
This is providing a driver of change in how many anti-counterfeit programs operate. There
are some companies that in the face of this pressure see no option to reduce the spend on
anti-counterfeit activity. This is far from ideal but is justified in the face of unclear pay-offs
and budgets in general being routinely scrutinised and under pressure. Time, it seems, is
running out on some programs to prove a clear benefit to the wider business.
However, in other companies this has been avoided by a commercial pragmatism.
Assumption-reliant ROI models are not required when there are tangible cashflows
generated by anti-counterfeit measures.
Rather than acting independently of the core business, these successful anti-counterfeit
programs are increasingly needing to mesh into other parts of the business but particularly
the sales and marketing functions. It can be a symbiotic relationship with the sales function.
The anti-counterfeit program focuses on identifying significant lost sales that can ultimately
be then readily directed into the legitimate sales channels. In return, the anti-counterfeit
benefit can be much more clearly measured in an uplift in genuine product sales. Rather
than a cost activity, it becomes an additional approach for ultimately increasing company
sales.
Similarly with marketing, for those companies to openly declare war on counterfeits it is a
distinct opportunity to grab the attention of customers. In its most effective guise, this is to
convey the unique value features of the genuine product over inferior fakes.
This leads into another trend in anti-counterfeit programs – for them to come out of the
shadows and be much more visible to key stakeholders. Historically most, but not all, brands
were reluctant to talk openly about fake versions of their products and aimed to tackle the
problem away from wider view. This is changing. As an economic problem with high margins,
some brand owners are realising that focusing all their effort on criminal counterfeit
production and supply is not going provide the results they seek. They must also look to
tackle the problem from the demand side.
As such, engagement of stakeholders is now at the vanguard of anti-counterfeit programs. It
is a natural progression to enhance and provide cost efficiencies to the existing areas, and
can be as discreet or as public as a brand sees appropriate. Stakeholder engagement itself
has long been a part of anti-counterfeit including mobilising employees and external law
enforcement such as customs. However, what is now growing is a willingness to engage with
customers and distributers to raise awareness and to mobilise a much broader combined
front.
Another problem brand owners have is the growth in data they capture from the Internet
with regards to suspicious activity. This is difficult to process quickly in order to prioritise
targeted evidence-based investigations.
Artificial intelligence is likely to make significant progress in this area in the coming years. A
decade ago, it was common for counterfeit products offered online to show clear indicators
such as spelling errors in photographs. These types of defects are far less common and
online sellers tend to now use stock images in any case. It means that a range of other
indicators have been sought out instead to identify high-risk sellers. These indicators lend
themselves very well to being processed by AI tools.
Whilst Amazon’s efforts to reduce fake offers to date have been frustrating, it is likely they
are the front runner of using machine learning to identify fake sellers, along with the Alibaba
Group. The volume of proprietary data they have to learn from is vast and third-party
technology providers cannot replicate their speed of learning and increasing effectiveness.
Numerous other online platforms are no doubt progressing as well. Eventually, these AI tools
may be made available to use outside the platforms they are developed in.
Within the next three to five years, we should start to see a dramatic impact of AI on the
availability of fake products being sold on major shopping and social media platforms. We
should also see much greater efficiencies in identifying high-value targets that justify
determined enforcement. However, brand owners will probably have to accept a lack of
control or access to the most effective AI tools for some time and be heavily reliant on the
big data-rich companies.
There will be numerous new AI tools from smaller technology companies which will try to
mirror this learning. However, their progress will be limited by the volume of data they can
gain access to. Some AI providers will offer to access a brand owner client’s data. However,
we are already seeing many companies such as Apple banning company use of ChatGBT
because of the risk of it dispersing trade secrets and other valuable company data. The
notion that a brand could give access to an AI tool which then learns from the data and takes
that out into the wider market should pose too great a risk to be viable for many.
In the near future, AI will at least clear the landscape of a great deal of counterfeit noise,
automate and improve lower value activities allowing the anti-counterfeit professionals to
focus their time on the highest value processes. However, AI alone will not win the war
against counterfeits.
Tim Waring is Founder and CEO of Netmonita and has been working on anti-counterfeit
programs since 2008.
Published By :
Tim Waring
CEO of Netmonita
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