Increase repeat purchases  faster.

Keep shoppers buying with powerful predictive models that activate your retail data to deepen engagement and repeat purchase — so you can focus on capturing every revenue opportunity.

The problem:

Most shoppers only buy once from a brand. As paid media costs climb and site traffic trends fluctuate, marketers need to prioritize the customers they have to predict which products they might buy next — and when and where to recommend them.

This is a constant headache for marketers. Here’s what it looks like:

Planning cross-functional meetings

Start planning your cross-functional meetings.

First, you have to get a list of one-time or lapsed buyers from your analytics team (if you have one) and ask your data science department for individual recommendations (again, if you have one).
Guess around products and offers

Venture a guess around products and offers.

Now, going on your best marketing instincts and the sprawling data you’ve collected, try to determine the next best offer for each of your buyers — and which channel to use to send it to them. Then hope that’s where they want to buy.
How many campaigns is too many

How many campaigns is too many?

You could try to calculate the best time to send each and every individual offer … or … you could just send them all at once and hope for the best.
Get your segments in order

Get your segments in order.

Create your static lists with all this info you’ve either inferred or stitched together — and load those into your ecommerce, email, SMS, and paid media tools to communicate with shoppers.
Tap creative to build templates

Tap creative to build templates … again.

Start building templates for each message and channel, which typically takes weeks given the limited scale of creative resources.
Planning cross-functional meetings

Start planning your cross-functional meetings.

First, you have to get a list of one-time or lapsed buyers from your analytics team (if you have one) and ask your data science department for individual recommendations (again, if you have one).
Guess around products and offers

Venture a guess around products and offers.

Now, going on your best marketing instincts and the sprawling data you’ve collected, try to determine the next best offer for each of your buyers — and which channel to use to send it to them. Then hope that’s where they want to buy.
How many campaigns is too many

How many campaigns is too many?

You could try to calculate the best time to send each and every individual offer … or … you could just send them all at once and hope for the best.
Get your segments in order

Get your segments in order.

Create your static lists with all this info you’ve either inferred or stitched together — and load those into your ecommerce, email, SMS, and paid media tools to communicate with shoppers.
Tap creative to build templates

Tap creative to build templates … again.

Start building templates for each message and channel, which typically takes weeks given the limited scale of creative resources.

You’re left with:

thumbs down  ~ 80% of shoppers only buying one time
thumbs down  slow payback on acquisition costs
thumbs down  low margins from heavy discounting

Bluecore makes it easy to keep your shoppers

coming back.

Leverage billions of data points across hundreds of brands.

Bluecore’s retail data model processes 500M products and attributes, 5B shopper identities, and 300B behaviors — all of which change and grow as powerful predictive models analyze data for best results.

With the most expansive dataset and accurate predictive models, drive your most important retail objectives, from retention and product discovery to churn prevention and margin preservation.

Never miss a revenue opportunity with built-in predictive models.

With an audience builder that enables you to use built-in predictive models in a few clicks, you can apply Bluecore’s extensive retail data and predictive models to any campaign — in seconds.

Determine the best shoppers to contact, the best content, offers, and recommendations to send each one, and the best time to reach them on the best channel for them — to quickly drive revenue.

Built-in predictive models

Extend intelligence in an open and integrated platform.

Use Bluecore’s built-in models and predictive audiences in your other systems — plus bring your own models into Bluecore’s platform — for a two-way street of seamless integration.

Extend models and predictive audiences into your existing CDP, data warehouse, data lake, or into other channels — and never be limited by black-box “intelligence.”

Extend intelligence in an open and integrated platform

The Bluecore result:

thumbs up  23% ↑ repeat buyers
thumbs up  3x ↑ ecommerce revenue
thumbs up  21% ↑ AOV

Retailers that are bringing this to life.

Sephora

Sephora
Sephora wanted to accelerate and deepen shopper loyalty. They put their retail data to work by easily enhancing their campaigns with Bluecore’s predictive “next best category” model — piquing shoppers’ interest in new products and categories for increased revenue and conversion .

Result:
8.4% ↑ revenue per client

6.3% ↑ conversion per client

City Furniture

City Furniture

CITY Furniture drove repeat purchases and brought inactive shoppers back into the fold by creating targeted audiences and by leveraging the category and discount affinity models built directly into their campaign workflows — to intelligently match each shopper to their perfect next home product.

Result:
118% ↑ repeat buyers | 30% ↑ active buyers

Start driving repeat purchases — fast.

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