Giuffrè Francis Lefebvre is one of the largest Italian players in the field of professional publishing.
Born from the merging in 2018 of the historic publisher Giuffrè Editore and Memento Francis Lefebvre, it is part of the international Lefebvre Sarrut group, active throughout Europe with 8 subsidiaries and more than 2,600 employees.
Giuffrè Francis Lefebvre provides high-quality tools, management software and information solutions, based on authoritative sources and reliable methods, to accompany professionals in the legal, tax, labor and corporate sectors.
The analysis of the online shop catalogue resulted in the outline of the characteristics of 4 audience types.
For each one, a tailor-made strategy was defined on the various channels with multiple conversion funnels, particularly on social media.
Our first step was to analyse past spending adv data and targets. This analysis led us to review the choice of the media mix not only in terms of the percentage of spending per channel, but also in the choice of channels and their use.
Two pillars guided our decisions: the elimination of the less productive channels in terms of conversions to strengthen those with greater possibilities for development; the focus on those channels which, in addition to their current positive performance, allow a better combination of target, use habits and product offer. The new media mix aimed to maximise and optimise the best performing channels (first and foremost Google) and to explore the management of other social media and channels with new approaches.
Google requires a very analytical approach and continuous study; our approach to this channel is characterised by targeted tailoring in the organisation of the account, as well as an active and constant analysis of the evolution of the KPIs (ROAS above all) in correlation with the opportunities highlighted by the most technical competitive metrics available on the platform (% coverage, ranking Vs competitors, quality scores, etc.).
Google provided the best performance data, and due to the nature of the product and the identified target, it was the best channel to invest in.
Looking at each channel more in detail:
Here we focused in particular on product categories with a medium shopping cart and a higher marginality.
At the targeting level, we adopted a combined strategy of specific keywords and dynamic targeting (DSA), a convenient solution especially for ecommerce of this size and inventory dynamism.
In this way, we will obtain an ideally total coverage of potential relevant traffic (also achieved by a strong focus on search term reports and consequently negative keywords), and then differentiate efforts according to data analysis.
In particular, we exploited the functionalities of Lengow, the leading ecommerce site automation platform, in relation to Google search campaigns, to integrate in real-time the performance (trend of visits and sales) of the products to the Feed itself and to automatically manage certain key tasks (adding/putting down products according to stock, updating prices, reporting 'hot' products).
The first step was the optimisation of the Google Merchant Centre. We made sure that the quality was impeccable (including aspects usually neglected such as return policies and the correct completion of all business info, shipping details and 'verification' of these by order documentation, etc).
We then focused on the FEED for the Merchant Centre (also using the Lengow platform), optimising all existing attributes and enhancing the feed with optional advanced fields (both in terms of Ads and Organic), such as: type, price range, best-seller, trending, in promo, seasonality, etc. (performance data is automated thanks to the Lengow-Analytics link).
The choice of this unusual channel comes from the preliminary analysis made on the target audience, providing a new focus that is supporting the growth of online shop sales with campaigns on the search network and with shopping campaigns.
The planning with audio spots is part of the strategy to expand the brand on younger targets, intercepting it on a platform that is increasingly used by various targets and that allows an interesting thematic segmentation.
Retargeting coverage is planned to be divided into 3 parts, in order to cover the widest spectrum of quality online placements. In this way, it will also be possible to compare (via Analytics) the 3 different performances and possibly adjust the allocations accordingly.
The affected placements are 3:
The unique RTB House engine based on Deep Learning algorithms identifies potential buyers and improves performance through ultra-personalised 1:1 retargeting, up to 50 per cent more efficient than standard Machine Learning AI-based approaches.
This activity would be developed directly by Facebook and LinkedIn Business Managers with targeted advertisements and to complement the funnels created and validated in the previous point on social ads.
Using an A/B test approach and several pilot campaigns, each channels and their performance were monitored, as well as the individual creatives and targets, so that any changes or exclusions could be made to the channel mix or individual ads.
In addition, comparing the data from the last 12 months with the previous ones, we found an asymmetry between the growth in traffic and the increase in conversions.
In order to improve cart abandonment rates, we acted on several fronts: we solved critical issues in the payment system, especially with regard to the overall UX of the payment process phase. More generally, we revised the UI for mobile devices and resolved technical criticalities concerning the overall page loading speed. To improve the overall user experience, with a direct impact on conversion rate and shopping cart abandonment rate, we adopted both UX and user flow analysis tools (hotjar) and optimisation and A/B testing tools (google optimise).
We implemented rigorous tracking using Google Tag Manager, so as to categorise paid effort traffic into the appropriate channels and then make individual 'campaigns' uniquely identifiable and comparable in the appropriate Analytics report.
Furthermore, in line with the agreed goals and kPIs, we developed a customised reporting dashboard using Google Data Studio, through which it was possible to easily create data reports from a wide range of sources and channels, including Google Ads, Analytics, Display & Video 360, Search Ads 360, File flat through CSV file uploads, and social media platforms such as Facebook and Instagram.