Developing a successful Amazon Advertising strategy requires a solid budget to support your campaign. Many brands rely heavily on numbers for budget forecasting. Quantitative data is essential to the process, but it won’t provide a clear, well-studied forecast on its own. Qualitative data, like intuition and industry knowledge and trends, can help you interpret the numbers. Together, they bring your budget forecast into sharper focus.
In our latest Amazon webinar, Preston Keaton (Director of SEM) and Sok Khann (SEM Specialist) discuss effective forecasting and the importance of both qualitative and quantitative data for this process.
Published on May 2, 2017.
Note: On September 5, 2018, Amazon rebranded its advertising platform. Amazon Marketing Services changed to Amazon Advertising and Amazon Advertising Platform changed to Amazon DSP, among other changes. This webinar was created before Amazon rebranded.
In this webinar, Preston and Sok talk about:
- The art and science of Amazon Marketing Services budget forecasting
- Qualitative data and quantitative data for Amazon Marketing Services campaigns
- Common Amazon Marketing Services budget forecasting scenarios
- How to use Google keyword tools to help your Amazon Marketing Services campaigns
Preston Keaton – Director of SEM, content26
Preston joined content26 in 2016. Prior to joining the team, he worked in digital marketing for nearly 10 years with a focus on SEM marketing. When he’s not busy optimizing campaigns, he has his hands full with his two little boys, Tyson and Cooper!
Sok Khann – SEM Specialist, content26
Sok joined content26 in 2016. He brings six years of digital marketing experience working for both agency and in-house marketing teams. When he’s not thinking about new ways to increase ROAS, he keeps himself busy by trying to keep up with his toddler, Juniper. In his free time, he enjoys reading about local concerts that he didn’t attend because he no longer has the energy to stay up past 9.00 p.m.
Register to view an on-demand version of this webinar