Partner spotlight: An interview with Artefact on Amazon Marketing Cloud

Artefact is a data-driven services company specializing in consulting on data transformation and digital and data marketing. Founded in 2014 by entrepreneurial engineers who saw the future written in data, our journey began with providing data marketing services. In 2017, we joined forces with Netbooster Group, one of the largest digital agencies in Europe, and further expanded our marketing delivery capabilities.

Currently, Artefact sits at the intersection of consulting, marketing and data science, and has a global presence with 16 offices in 13 countries across Europe, Asia, Americas and Africa. We provide data-driven solutions built upon deep data science and AI technology, and offer a wide range of services such as data strategy, data governance, precision marketing and multi-channel campaign management. We put consumers at the heart of companies’ digital transformation strategies, and help our clients turn data into business impact by delivering tangible results across the entire value chain.

Advising on brands’ e-retail strategies and helping them sell online more effectively has been one of our top strategic objectives over the past years, especially during the COVID-19 period. Collaborating with Amazon Ads, and AMC specifically, is a big step forward in leveraging multiple signal sources and forming new insights to fuel both marketing and category management.

AMC is an important asset for Artefact and our clients for three main reasons:

• Providing access to Amazon Ads event-level signals such as engagement and ad-attributed sales. This allows us to build deeper analysis to help inform retail media activation and improve return on ad spend (ROAS).
• Enabling the mix of first-party information with Amazon Ads signals in a privacy-safe environment. This helps us better understand brand customer behaviours across the shopping journey, and adapt marketing strategies accordingly.
• Supporting the option to onboard beyond just marketing events. This helps us to progressively address additional use cases on topics such as sales and product cost structure.

• Analyse the campaign recency to help ensure optimal performance
• Understand the frequency capping impact on sales by audience segments
• Identify the ideal media mix to reach audiences using Amazon DSP

We recommend a four-step approach:

1. AMC set-up:
   At Artefact, we support brands to activate AMC instance and facilitate the aggregation of different signals including Amazon Ads signals and advertisers’ first-party signals. In addition, signal quality assessment is strategic to ensuring input relevancy and later analysis consistency.
2. Map use cases:
   Depending on brand’s business context and challenges, different analysis can be run through AMC. Artefact have built a library of use cases on audience, measurement and operations. This allows us to quickly prioritise relevant projects based on brand’s needs.
3. Test and learn:
   We recommend a super agile approach, by starting with basic use cases on small scale (e.g. one brand/product type x one country), learn from it, make optimisation and quantify business impact. This step can help us quickly capture learnings and identify use cases that can be scaled.
4. Scale:
   Leveraging insights from step three, scaling enables Artefact and brand teams to deploy a wider scope of use cases and utilise them to further augment business impact for a broader set of products and countries.

To succeed in working with AMC, we recommend brands to pay attention to the following areas:

• Skills – Build a hybrid team composed of business personnel who understand the brand strategy, media experts managing advertising campaigns and data analysts with tech competencies.
• Organisation – Adopt an agile methodology by working in sprints to quickly get learnings out of the initial AMC use cases, review them with the advertising team, test their efficiency and scale for broader adoption and optimisation.
• Event signals – Onboard all relevant first-, second- and third-party information to explore new use cases using richer signals
• Tech – Apart from using the standard instructional queries, also build your own query library to enable easy repeat usage and scaled application at all campaigns and countries.