Personalization platforms

Personalization platforms (Dynamic Yield, RetailRocket, Mindbox, and others) show different content to different users: product recommendations ("bought together", "you may also like"), personal banners and selections, dynamic blocks and search/merchandising by behavior, history and segment. We implement the platform, catalog and event passing, recommendation blocks, rules and A/B tests, and the analytics link. Honestly about the main point: personalization is an amplifier, not a source of demand. It helps where there is already traffic, an assortment and behavior history; on empty or very low traffic it works poorly due to the "cold start" — the system has nothing to learn from, and recommendations will be weak until data accumulates. The recommendations themselves are probabilistic: the algorithm guesses by similarity and behavior, and sometimes misses — that is normal, perfect relevance does not exist. A conversion uplift is possible but not guaranteed in percent: the honest way to be sure is an A/B test (part of the audience sees personalization, part does not), and we set it up rather than promising "+30%". A clean catalog and data are needed: if product data is dirty or there are few events, recommendations will be poor (garbage in, garbage out). The platform is a subscription, the tariff depends on traffic and features and is your cost; and it can grow in steps as traffic and events grow, not linearly — check the tariff terms in advance so that success does not blow up the budget. Our price is for the implementation. Personalization works on behavioral data — that is personal data, consent and a correct policy are needed (152-FZ; GDPR abroad), and that is on you; note that some platforms (especially foreign ones) store data outside the RF — that matters for 152-FZ, and for RF data we will pick with residency in mind. And when you switch platforms, the accumulated models and configured recommendation blocks usually do not transfer (vendor lock-in) — check exportability in advance. And honestly about moderation: over-personalization creates a "bubble" and annoys — a few accurate blocks beat everything at once. If you have little traffic, a narrow assortment or no history, personalization is premature — start with analytics and basic recommendations, and we will say so. Picture this: a regular customer sees on the homepage the categories they browse and a selection tied to their past orders, while a new one sees bestsellers; everyone sees a more relevant storefront. The base price starts from 40,000 ₽; it depends on the platform, the number of blocks, the catalog and your system.

• Everyone sees the same storefront, ignoring interests and history.
• Product recommendations are not set up or show irrelevant items.
• Regular customers do not feel recognized and leave for competitors.
• You do not know whether personalization has any effect — there is no honest test.

• Implementing a personalization platform (Dynamic Yield / RetailRocket / Mindbox)
• Catalog and event passing, recommendation blocks
• Personal banners, selections and dynamic blocks
• Personalization rules and A/B tests to verify the effect
• An analytics link and relevance control
• Highlighting consent requirements for behavioral data (152-FZ)
• An honest assessment of traffic and catalog readiness (cold start)
• An honest assessment of whether you need personalization at your stage

• A more relevant storefront and recommendations for different users
• The effect is verified by an A/B test, not by a promise of percentages
• Regular customers feel recognized
• It is clear where the tech ends and your traffic, catalog, data and consent begin

• We clarify the platform, blocks, catalog and traffic state
• We connect the platform, data passing and recommendation blocks
• We launch an A/B test, assess the effect and tune the rules

• Will personalization raise conversion?

  It may, but the percentage is not guaranteed. The effect depends on traffic, assortment and data quality. The honest way to be sure is an A/B test: part of the audience sees personalization, part does not, and we compare. Promising "+30% to conversion" without a test would be dishonest — we set up the check rather than draw numbers.

• Will it work right after connecting?

  Not at full strength. The algorithms need a data-collection period and traffic to learn — this is the "cold start". On low traffic or a new site, recommendations are weak at first and improve as history accumulates. If there is almost no traffic, personalization is premature for now — we will honestly say so.

• How much does it cost and what about the data?

  A personalization platform is a subscription, its tariff depends on traffic and features — that is your cost; our price is for the implementation. Personalization works on behavioral data — that is personal data, consent and a correct policy are needed (152-FZ), the legal side is on you, we help technically.