Multi-Channel Marketing Campaigns

Patent metadata

Field	Value
Publication number	US-2016148248-A1
Application number	US-201414553911-A
Country	US
Kind code	A1
Filing date	Nov 25, 2014
Priority date	Nov 25, 2014
Publication date	May 26, 2016
Grant date	—

Abstract

Techniques for multi-channel marketing campaigns are described herein. The techniques enable marketers to determine sequences of chronologically ordered communication channels by which to perform a multi-channel marketing campaign. In some cases, the techniques determine a sequence likely to have a positive result based on historic marketing sequence data and a desired category of the marketer's campaign. The techniques may also determine some number of trial sequences for a trial marketing campaign and then determine a best sequence for a full-scale marketing campaign based on the success of the trial sequences during the trial marketing campaign.

First claim

What is claimed is:

1 . In a digital media environment for determining a sequence of digital or mixed digital and non-digital communication channels for use in a digital or mixed multi-channel marketing campaign based on digital information concerning the digital and non-digital communication channels, a method comprising:
receiving historic marketing sequence data for multiple sequences, each sequence indicating communication channels included in the sequence, an order for those communication channels in the sequence, a category of the sequence, and a success of the sequence; receiving a desired category for a desired multi-channel marketing campaign; correlating the desired category to one or more categories of the sequences of the historic marketing sequence data; and determining a sequence for the desired category for the desired multi-channel marketing campaign, the determining based on the correlation between the desired category and the success of the one or more categories of the sequences of the historic marketing sequence data, the sequence for the desired category including multiple determined communication channels and a determined order for the multiple determined communication channels.

2 . The method as described in claim 1 , wherein the desired category indicates a type of product, relationship, interaction, or service.

3 . The method as described in claim 1 , wherein the success of the multiple sequences of the historic marketing sequence data is a sale or failure to sell a product.

4 . The method as described in claim 1 , wherein the success of the multiple sequences of the historic marketing sequence data is a continuation or cessation of a relationship.

5 . The method as described in claim 1 , wherein the desired communication channels are automated or digital.

6 . The method as described in claim 1 , wherein determining the sequence is further based on a desired demographic of persons for the desired multi-channel marketing campaign and demographics data of the historic marketing sequence data.

7 . The method as described in claim 1 , wherein determining the sequence for the desired category for the desired multi-channel marketing campaign determines a dynamic sequence, the dynamic sequence having one or more alternative options by which to adjust the communication channels based on an interaction or lack thereof by a user of the dynamic sequence during the desired multi-channel marketing campaign.

8 . The method as described in claim 7 , wherein determining the dynamic sequence aggregates multiple sequences sharing a common communication channel.

9 . In a digital media environment for determining a best sequence of digital or mixed digital and non-digital communication channels for use in a digital or mixed multi-channel marketing campaign based on digital information concerning the digital and non-digital communication channels and success of multiple trial marketing sequences, the method comprising:
determining multiple trial marketing sequences, each of the trial marketing sequences having a same desired category and different communication channels or orders for communication channels; performing, in a digital media environment, a trial multi-channel marketing campaign with the multiple trial marketing sequences, the performing including:
recording success for each of the trial marketing sequences; and
determining a best sequence based on the recorded success for each of the trial marketing sequences; or
determining a subset of the trial marketing sequences based on having a higher success relative to trial marketing sequences not of the subset;
performing a second trial multi-channel marketing campaign in the digital media environment with the subset of the multiple trial marketing sequences, the performing of the second trial including recording success for each of the subset of the trial marketing sequences; and
determining, based on the recorded success for each of the subset of the trial marketing sequences, a best sequence of the subset of the trial marketing sequences.

10 . The method as described in claim 9 , wherein determining the multiple trial marketing sequences is based on historic marketing sequence data for multiple historic sequences, the historic marketing sequence data indicating communication channels, order for the communication channels, categories, and successes.

11 . The method as described in claim 9 , wherein performing the trial multi-channel marketing campaign with the multiple trial marketing sequences is performed multiple times, each time with a different demographic of persons, and wherein determining the best sequence is specific to one of the different demographics.

12 . The method as described in claim 9 , wherein determining the best sequence based on the recorded success for each of the trial marketing sequences or based on the recorded success for each of the subset of the trial marketing sequences comprises determining a dynamic sequence, the dynamic sequence having one or more alternative options by which to adjust the communication channels based on an interaction or lack thereof by a user of the dynamic sequence.

13 . The method as described in claim 12 , wherein determining the dynamic sequence aggregates multiple sequences sharing a common communication channel.

14 . In a digital media environment for determining a best sequence of digital or mixed digital and non-digital communication channels for use in a digital or mixed multi-channel marketing campaign based on digital information concerning the digital and non-digital communication channels and success of multiple trial marketing sequences, the method comprising:
receiving selection of a desired category for a desired multi-channel marketing campaign; determining trial marketing sequences for the desired category based on a statistical measure of confidence for the trial marketing sequences, the statistical measure of confidence based on historic marketing sequence data for multiple sequences and the desired category, the trial marketing sequences having different communication channels or orders for communication channels; performing, in a digital media environment, a trial multi-channel marketing campaign with the trial marketing sequences, the performing including recording success for each of the trial marketing sequences, the recording performed both digitally and without user interaction; and determining, responsive to a statistically relevant quantity of successes being recorded for the trial marketing sequences during the trial multi-channel marketing campaign, a best sequence of the trial marketing sequences based on the statistically relevant quantity of recorded successes.

15 . The method as described in claim 14 , further comprising presenting, in a user interface and prior to receiving selection, multiple, selectable categories for the desired multi-channel marketing campaign and wherein receiving selection of the desired category is received through the user interface.

16 . The method as described in claim 14 , wherein determining the trial marketing sequences comprises correlating the desired category to a same category of sequences of the historic marketing data for multiple sequences.

17 . The method as described in claim 14 , wherein determining the trial marketing sequences comprises correlating the desired category to multiple similar categories of sequences of the historic marketing data for multiple sequences.

18 . The method as described in claim 14 , wherein the trial ma

Assignees

• Adobe Systems Inc

Inventors

• Sinha Ritwik
• Mehta Sanket Vaibhav
• Bohra Tapan
• Krishnan Adit

Classifications

• G06Q30/0243 Primary

  Comparative campaigns · CPC title